doctor of philosophy april , 201 3 · miloš crnjanski, sumatra. ii abstract pollution in the...

Queensland University of Technology

Investigation of the Chemical and Physical Basis of

Oxidative Stress Generated by Particulate Matter Using

the Profluorescent Probe Technique

Svetlana Stevanovic

A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS OF THE DEGREE OF

DOCTOR OF PHILOSOPHY

April, 2013

i

Each love, each morning in a foreign land

Envelops our soul closer by its hand

In an endless tranquillity of blue seas,

In which red corals glitter

like the cherries of my homeland.

Miloš Crnjanski, Sumatra

ii

ABSTRACT

Pollution in the atmosphere involves the presence of many components including

gases, vapours, smoke and dust (aerosols). Of these components, one factor that can have

major significance is the presence of fine and ultra fine particles that can be harmful to

human health. Over the last decade the epidemiology of human exposure to ambient

particulate matter has clearly established a statistically significant correlation between

levels of fine particles and negative health effects. Studies have now been carried out in

several countries and the results have consistently shown a significant impact on human

health that is attributable to ambient particles. Within such particles, the fine particulate

matter fraction smaller than 2.5 µm (PM 2.5) has been linked to a range of respiratory and

cardiovascular health problems because of their long lifetimes in the air (small particles

have very long settling times) and respiratory deposition characteristics (they deposit

deeper in the lungs). A number of epidemiological studies have shown that PM 2.5 is

correlated with severe health effects, even including enhanced mortality. Despite this clear

correlation, the main question that still remains unanswered is: What are the underlying

toxicological mechanisms by which fine and ultrafine particles induce adverse health

effects?

Among a number of hypotheses, oxidative stress and inflammation are leading

contenders to explain the observed effects. Fine and ultrafine particles may cause the

production of reactive oxygen species (ROS) within lung epithelial cells, and possibly within

the cells of other organs including the endothelial cells of arteries. Once they are generated

within the cell, ROS are responsible for driving oxidative stress at sites of deposition and

thereby triggering a cascade of events associated with inflammation and, at higher

concentrations, even cell death.

An in-house methodology for assessing PM-related ROS activity has been recently

developed. A profluorescent nitroxide probe, BPEAnit, was used to measure the oxidative

potential of combustion generated aerosols and the probe proved to be sufficiently robust

and sensitive enough to provide reliable and rapid estimates of the oxidative potential of

PM.

iii

During the course of this project mechanisms behind the BPEAnit fluorescence increase

upon exposure to diesel and biodiesel PM were analysed. The main product responsible for

the fluorescence measured was identified and isolated, which aided the interpretation of

results and prevented the possible underestimation of ROS content.

Also, it was determined that the redox properties of particles depend on the semi-volatile

organic fraction residing on the particle surface, but that the nature of this relationship

varies with the source of the particles. Although a clear link exists in all the cases, with

biodiesel PM it was shown that the relationship between these two parameters is complex

and that the oxygenated organic component is the aspect that shows the best correlation

with levels of ROS activity.

Finally, different biodiesel stocks were tested to investigate the differences in the physico-

chemical properties of emissions after their combustion in a modern common rail diesel

engine. For all four biodiesel fuels and their blends tested it was demonstrated that

oxidative potential (OP) of their emissions as well as their physical characteristics is

ultimately coupled to the molecular structure of the fuel, specifically oxygen content, chain

length and the level of unsaturation.

iv

KEYWORDS

Combustion aerosols, combustion-generated particulate matter, diesel exhaust,

biodiesel exhaust, health aspects of aerosol, health effects of particulate matter, free

radicals, reactive oxygen species, ROS, oxidative stress, oxidative potential, inflammatory

potential, in vitro, profuorescent nitroxides; BPEAnit; fluorescence, thermodenuder,

diffusion dryer, diffusion losses, oxygenated organic aerosols, volatility, oxidative capacity,

vi

Table of contents

ABSTRACT ............................................................................................................. ii

KEYWORDS .......................................................................................................... iv

STATEMENT OF ORIGINAL AUTHORSHIP ................................................................ v

LIST OF PUBLICATIONS ........................................................................................ xii

LIST OF TABLES .................................................................................................. xiii

LIST OF FIGURES ................................................................................................. xiii

ACKNOWLEDGEMENTS ....................................................................................... xx

ABBREVIATIONS ................................................................................................. xxi

Chapter 1 ..................................................................................................................... 1

INTRODUCTION .................................................................................................... 1

1.1. Description of scientific problem investigated ......................................... 1

1.2. Overall aims of the study ........................................................................ 2

1.3. Specific objectives of the study ............................................................... 3

1.4. Account of scientific progress linking the scientific papers ....................... 4

Chapter 2 ..................................................................................................................... 7

LITERATURE REVIEW ............................................................................................. 7

2.1. Particle size distribution and composition ............................................. 7

2.1.1 Background and definitions ............................................................................... 7

2.2. Combustion generated aerosol ............................................................. 10

2.2.1. Combustion.........................................................................................…...10

2.3. Nucleation and condensation ................................................................ 13

2.3.1.Role of atmospheric condensation ................................................................. 15

2.3.2.Dilution effects on non-labile PM components ............................................ 18

2.3.3.Dilution effects on semi-volatile PM components ....................................... 18

vii

2.4. Photochemical reactions of primary emissions and secondary organic aerosol

formation ........................................................................................................... 23

2.5. Combustion of diesel and biodiesel ....................................................... 25

2.5.1.Physical and chemical characteristics of DPM .............................................. 25

2.5.2.Physical and chemical characteristics of biodiesel PM ................................ 28

2.6. Free radicals and their generation in human body ................................. 30

2.7. PM toxicity and related health effects ................................................... 33

2.8. Particle sampling approaches for assessing PM toxicity ......................... 37

2.9. Measurement of the radical generating capacity of the particulate matter40

2.9.1 In vitro studies ........................................................................................... 40

2.9.2.Cell-free assays .......................................................................................... 41

2.9.2.1 DTT assay ................................................................................................ 43

2.9.2.2 Ascorbate- Dihydroxybenzoate Based Redox Activity .............................. 44

2.9.2.3 POHPAA assay......................................................................................... 45

2.9.2.4 DCFH assay.............................................................................................. 45

2.9.2.5 DHR-6G assay.......................................................................................... 47

2.10. Nitroxides as spin-trapping agents ........................................................ 48

2.10.1.Profluorescent nitroxides ............................................................................... 49

2.11. Application of profluorescent nitroxide for the detection of particulate matter

bound ROS ......................................................................................................... 51

2.11. Oxidative potential of ambient PM and redox properties of DEP and biodiesel

PM………. ............................................................................................................ 52

Chapter 3 ................................................................................................................... 68

APPLICATION OF PROFLUORESCENT NITROXIDES FOR MEASUREMENTS OF OXIDATIVE

CAPACITY OF COMBUSTION GENERATED PARTICLES ........................................... 68

Abstract …………………………………………………………………………………………………………………70

3.1. Introduction ................................................................................................ 71

viii

3.2. Methodology ............................................................................................... 72

3.3. Results and discussion ................................................................................. 75

3.4. Conclusion ................................................................................................... 78

3.4. Conclusion ................................................................................................... 78

3.5. Acknowledgments ....................................................................................... 79

3.6. References ................................................................................................... 80

Chapter 4 ................................................................................................................... 83

THE USE OF A NITROXIDE IN DMSO TO CAPTURE FREE RADICALS IN PARTICULATE

POLLUTION......................................................................................................... 83

Abstract. ............................................................................................................ 85

4.1. Introduction ................................................................................................ 86

4.2. Results and discussion ................................................................................. 87

4.3. Conclusion ................................................................................................... 93

4.4. Experimental section ................................................................................... 94

4.5. Acknowledgments ....................................................................................... 95

4.6. References ................................................................................................... 96

4.7. Supplementary Information ......................................................................... 97

Chapter 5 ................................................................................................................. 126

CHARACTERISATION OF A COMMERCIALLY AVAILABLE THERMODENUDER AND DIFFUSION

DRYER FOR ULTRAFINE PARTICLE LOSSES .......................................................... 126

Abstract …………………………………………………………..…………………………………………………128

5.1. Introduction .............................................................................................. 130

5.2. Experimental ............................................................................................. 131

5.2.1. a TSI Low-Flow Thermodenuder Model 3065 (TSI-TD) ........................... 132

5.2.2. Topas DDU 570/H diffusion dryer ................................................................ 131

5.2.3. Experimental description .............................................................................. 132

ix

5.2.4. Temperature Profiles ................................................................................... 133

5.3. Results and discussion ............................................................................... 133

5.3.1. Temperature Profile ....................................................................................... 133

5.3.2. Losses inside thermodenuder ....................................................................... 134

5.3.3. Losses inside diffusion dryer ......................................................................... 138

5.4. Conclusion ................................................................................................. 139

5.5. References ................................................................................................. 140

5.6. Supporting Material ................................................................................... 143

Chapter 6 ................................................................................................................. 145

A PHYSICO-CHEMICAL CHARACTERISATION OF PARTICULATE EMISSIONS FROM A

COMPRESSION IGNITION ENGINE: THE INFLUENCE OF BIODIESEL FEEDSTOCK ... 145

Abstract… ......................................................................................................... 149

6.1. Introduction .............................................................................................. 149

6.2. Methodology ............................................................................................. 151

6.2.1. Engine and fuel specifications ...................................................................... 151

6.2.2. Particulate emissions measurement methodology………………………………151

6.2.3. Data analysis ........................................................................................... 153


6.3.1. PM10 emission factors .................................................................................. 154

6.3.2. Particle number emission factors ................................................................ 155

6.3.3. Particle number size distributions ............................................................... 156

6.3.4. PAH emission factors and ROS concentrations .......................................... 159

6.3.5. Particle volatility and ROS correlation ......................................................... 161

6.3.6. Particle surface area and organic volume percentage of particles ......... 162

6.4. Acknowledgments ..................................................................................... 164

6.5. References ................................................................................................. 164

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Chapter 7 ................................................................................................................. 170

THE INFLUENCE OF OXYGENATED ORGANIC AEROSOLS (OOA) ON THE OXIDATIVE

POTENTIAL OF DIESEL AND BIODIESEL PARTICULATE MATTER ........................... 170

Abstract ……………………………………………………………………………………………………………171

7.1. Introduction .............................................................................................. 172

7.2.Experimental .............................................................................................. 174

7.2.1. Engine specifications ...................................................................................... 174

7.2.2. Fuels ................................................................................................................. 175

7.2.3. Particulate Emissions Measurement Methodology .................................. 176


7.3.1. Particle number size distribution ................................................................. 178

7.3.2. Total PM2.5 mass emissions and its organic fraction178

7.3.3. Correlation between oxidative potential and particle volatility .............. 180

7.3.4. The influence of oxygenated organic aerosols (OOA) content on the oxidative

potential of diesel particulate matter .................................................................... 182

7.4. References ................................................................................................. 186

Chapter 8 ................................................................................................................. 190

ENGINE PERFORMANCE CHARACTERISTICS FOR BIODIESELS OF DIFFERENT DEGREES OF

SATURATION AND CARBON CHAIN LENGTHS .................................................... 190

Abstract. .......................................................................................................... 193

8.1. Introduction .............................................................................................. 193

8.2. Experimental set-up ................................................................................... 197

8.2.1. Test Facility ...................................................................................................... 197

8.2.2. Fuel Selection ......................................................................................... 200


8.3.1. Engine performance ............................................................................... 203

xi

8.3.2. Emission Characteristics ................................................................................ 207

8.4. Conclusion ................................................................................................. 213

8.5.Acknowledgments ...................................................................................... 214

8.6. References ................................................................................................. 215

Chapter 9 ................................................................................................................. 242

CONCLUSIONS .................................................................................................. 242

9.1. Principal significance of findings ................................................................. 243

9.2. Directions for future research .................................................................... 248

xii

LIST OF PUBLICATIONS

S. Stevanovic, Z.D. Ristovski, B. Miljevic, K. E. Fairfull-Smith, S. E. Bottle, Application of

profluorescent nitroxides for measurement of oxidative capacity of combustion generated,

CI&CEQ 18 (4) 653−659 (2012) 653

S. Stevanovic, B. Miljevic, G.K. Eaglesham, S. E. Bottle, Z. D. Ristovski, K. E. Fairfull-Smith, The

Use of a Nitroxide Probe in DMSO to Capture Free Radicals in Particulate Pollution,

European Journal of Organic Chemistry, 012. 2012(30): p. 5908-5912.

S. Stevanovic, B. Miljevic, P. Madl, S. Clifford, Z.D. Ristovski, Characterisation of a

commercially available thermodenuder and diffusion drier for ultrafine particles losses,

submitted to Aerosol Science and Technology

Surawski, N. C.; Miljevic, B.; Ayoko, G. A.; Elbagir, S.; Stevanovic, S.; Fairfull-Smith, K. E.;

Bottle, S. E.; Ristovski, Z. D., A physico-chemical characterisation of particulate emissions

from a compression ignition engine: the influence of biodiesel feedstock, Environmental

Science & Technology 2011. 45(24): p. 10337-10343.

S. Stevanovic, Z.D. Ristovski, B. Miljevic, K. E. Fairfull-Smith, R.Brown, S. E. Bottle, The

influence of oxygenated organic aerosols (OOA) on the oxidative potential of diesel and

biodiesel particulate matter, Environmental Science & Technology 2013 47(14): p. 7655-62

P.X. Pham, T.A. Bodisco, S. Stevanovic, M.D. Rahman, A. Pourkhesalian, W. Hao, Z.D.

Ristovski, R.J. Brown , A.R. Masri, Engine Performance Characteristics for Biodiesels of

Different Degrees of Saturation and Carbon Chain Lengths , SAE Int. J. Fuels Lubr., 2013, 6 (1)

xiii

LIST OF TABLES

Table 2-1. Particle dynamics and behaviour. ............................................................ 17

Table 4-1. . Identification of adducts of nitroxide 1 using HPLC/MS.. .................... 88

Table S 4-1. Particle emissions during biodiesel sampling ...........................................

LIST OF FIGURES

Figure 2-1. Typical engine exhaust size distribution both mass and number weightings are

shown ........................................................................................................................... 9

Figure 2-2. Illustration of the fate of exhaust particles in the atmosphere and how the

processes of nucleation, condensation, and adsorption affect the formation, dispersion and

deposition of exhaust aerosol ..................................................................................... 15

Figure 2-3. Fuel-based organic aerosol emission factor as a function of their

concentrations and dilution ratios (Robinson, Donahue et al. 2007) ......................... 21

Figure 2-4. Vapour pressures of organic compounds as a function of carbon number and

functionality (Jacobson, Hansson et al. 2000).. ......................................................... 22

Figure 2-5. An engineer’s depiction of DPM ............................................................ 26

Figure 2-6. Scheme depicting connection between antioxidants and free radicals ... 32

Figure 2-7. . Simplified mechanism of quinoid redox cycling (QH2 – catechol) (Squadrito,

Cueto et al. 2001) ....................................................................................................... 35

Figure 2-8. Simulated EPR spectrum of the H2C(OCH3) radical ............................. 42

Figure 2-9. Chemical reaction between DTT and oxygen with PM as a catalyst ...... 44

Figure 2-10. Chemical reaction between DTT and oxygen with PM as a catalyst .... 45

Figure 2-11. Hydrolysis of DCFH-DA and ROS-induced oxidation of DCFH. ....... 47

xiv

Figure 2-12. Chemical basis of DHR-6G assay ............................................................ 48

Figure 2-13. The redox transformations between (from left to right) oxoammonium cation,

nitroxide and hydroxylamine ..................................................................................... 49

Figure 2-14. 9-(1,1,3,3-tetramethylisoindolin-2-yloxyl-5-ethynyl)-10-(phenylethynyl)

anthracene (BPEAnit) 50

Figure 2-15. Structures of some of the profluorescent nitroxides synthesised at QUT. In

these examples five membered nitroxide ring is covalently fused to: 1) 9,10-

bis(phenylethynyl)anthracene (BPEA); 2)9,10-diphenylanthracene and 3) phenanthrene

.................................................................................................................................... 52

Figure 3-1. Structures of some of the profluorescent nitroxides synthesised at QUT together

with the excitation and emission wavelengths of the fluorophores ......................... 74

Figure 3-2. Correlation between the amount of ROS and the amount of organics for stable

phase of cold-start (A), and warm-start (B) logwood burning. ................................. 76

Figure 3-3. The amount of ROS for stable phase of cold-start (A), and warm-start (B)

logwood burning, side stream tobacco smoke and different operating conditions for ethanol

blended diesel ............................................................................................................ 77

Figure 4-1. HPLC chromatograms from the reaction of nitroxide 1 (4 µM in DMSO) with

particulate matter derived from a compression ignition engine employing biodiesel, a)

absorbance at 430 nm, b) fluorescence detection λex = 430 nm, λem = 485 nm. ... 91

Figure 4-2. HPLC chromatograms of nitroxide 1 (10 mM in DMSO), a) absorbance at 430 nm,

b) fluorescence detection λex = 430 nm, λem = 485 nm. ......................................... 92

Figure 4-3. A Photoionisation (+ve mode) mass spectrum of the major HPLC component (at

5.16 min) from the reaction of nitroxide 1 (4 µM in DMSO) with particulate matter derived

from a compression ignition engine employing biodiesel. ........................................ 93

Figure S-1 4-8. Schematic representation of the experimental set-up for sampling aerosol

from a compression ignition engine employing biodiesel into impingers containing a solution

of the nitroxide 1 in DMSO (4 µM). ........................................................................... 94

xv

Figure S-2 4-8. Fluorescence increase by bubbling aerosol generated from a compression

ignition engine employing 100% soy diesel at half load at 1.0 L/min for 60 minutes through

an impinger containing 20 mL of a 4 µM solution of nitroxide 1 in DMSO ........ 105

Figure S-3 4-8. HPLC/MS data for 9-(1,1,3,3-tetramethylisoindolin-2-yloxyl-5-ethynyl)-10-

(phenylethynyl)anthracene 1.......... 106

Figure S-4 4-8 HPLC/MS data for 9-(2-methoxy-1,1,3,3-tetramethylisoindolin-5-ethynyl)-10-

(phenylethynyl)anthracene 4 .................................................................................... 107

Figure S-5 4-8 HPLC/MS data for 9-(2-acetoxy-1,1,3,3-tetramethylisoindolin-5-ethynyl)-10-


Figure S-6 4-8 HPLC/MS data from the sonication of 9-(1,1,3,3-tetramethylisoindolin-2-

yloxyl-5-ethynyl)-10-(phenylethynyl)anthracene 1 in DMSO ................................ 109

Figure S-7 4-8 . HPLC/MS data for 9-(1,1,3,3-tetramethylisoindolin-2-yloxyl-5-ethynyl)-10-

(phenylethynyl)anthracene 1 + NH2NH2.H2O ....................................................... 110

Figure S-8 4-8. HPLC/MS data for 9-(1,1,3,3-tetramethylisoindolin-2-yloxyl-5-ethynyl)-10-

(phenylethynyl)anthracene 1 + H2O2 ...................................................................... 111

Figure S-9 4-8 HPLC data for 9-(1,1,3,3-tetramethylisoindolin-2-yloxyl-5-ethynyl)-10-

(phenylethynyl)anthracene 1 + AAPH (anaerobic conditions) ................................ 112

Figure S-10 4-8 HPLC/MS data for 9-(1,1,3,3-tetramethylisoindolin-2-yloxyl-5-ethynyl)-10-

(phenylethynyl)anthracene 1 + PM (biodiesel)........................................................ 113

Figure S-11 4-8 1H NMR spectrum for 9-(2-acetoxy-1,1,3,3-tetramethylisoindolin-5-

ethynyl)-10-(phenylethynyl)anthracene 5 ................................................................ 114

Figure S-12 4-8 13

C NMR spectrum for 9-(2-acetoxy-1,1,3,3-tetramethylisoindolin-5-


Figure S-13 4-8 HPLC chromatogram (254 nm absorbance, 60% THF/40% water, 1 mL/min

flow rate, C18 column) for 9-(2-acetoxy-1,1,3,3-tetramethylisoindolin-5-ethynyl)-10-


Figure S-14 4-8. 1H NMR spectrum for 9-(2-methanesulfonyl-1,1,3,3-tetramethylisoindolin-

5-ethynyl)-10-(phenylethynyl)anthracene 3 ............................................................ 117

xvi

Figure S-15 4-8 . 13

C NMR spectrum for 9-(2-methanesulfonyl-1,1,3,3-tetramethylisoindolin-


Figure S-16 4-8 . HPLC chromatogram (254 nm absorbance, 60% THF/40% water, 1

mL/min flow rate, C18 column) for 9-(2-methanesulfonyl-1,1,3,3-tetramethylisoindolin-5-

ethynyl)-10-(phenylethynyl)anthracene 3. ............................................................... 119

Figure S-17 4-8 MS data (photo ionisation source) for 9-(2-methanesulfinyl-1,1,3,3-

tetramethylisoindolin-5-ethynyl)-10-(phenylethynyl)anthracene 3.......................120

Figure S-18 4-8 1H NMR spectrum for 9-(2-methanesulfinyl-1,1,3,3-tetramethylisoindolin-5-


Figure S-19 4-8 13

C NMR spectrum for 9-(2-methanesulfinyl-1,1,3,3-tetramethylisoindolin-


Figure S-20 4-8 HPLC chromatogram (254 nm absorbance, 60% THF/40% water, 1 mL/min

flow rate, C18 column) for 9-(2-methanesulfinyl-1,1,3,3-tetramethylisoindolin-5-ethynyl)-10-


Figure 5-1 Temperature profile of the TSI-TD at 0.5 and 1.5 L/min. At a flow-rate of 0.5

L/min (left) the heated bolus of air it is not pushed fast enough to the adsorber stage and as a

result cools off still within the desorber tube, while a flow rate exceeding 1 L/min (right)

results in very distorted temperature profiles.. ......................................................... 134

Figure 5-

room temperature and at three different flow rates (1 L/min, 2 L/min, 4 L/min). The full line

is the predicted losses in TSI 3065 based on the logistic regression model, with the dashed

line representing the 95% confidence intervals....................................................135

Figure 5-3 Particle number losses as a function of size for NaCl and lubricating oil particles

at 300 C and three selected flow rates (1 L/min, 2 L/min, 4 L/min).....................136

Figure 5-4. Measured size of pre-selected NaCl and lubricating oil particles before and after

L/min, 2 L/min and 4 L/min .................................................................................... 138

xvii

Figure 5-5. Open circles (○) indicate measured NaCl particle losses in Topas DDU 570/L

diffusion dryer for 1, 2 and 4 L/min, at room temperature. The full line is the predicted losses

based on the logistic regression model, with the dashed line representing the 95% confidence

intervals .................................................................................................................... 139

Figure 6-1. Brake specific PM10 emission factors (g/kWh) for the 14 fuel types investigated

in this study .............................................................................................................. 155

Figure 6-2. Brake-specific particle number emissions (#/kWh) for the 14 fuel types

investigated in this study.. ........................................................................................ 156

Figure 6-3. Particle number size distributions (corrected for dilution) for all fourteen fuel

types (top panel: soy feedstock, middle panel: tallow feedstock, bottom panel: canola

feedstock). TD denotes tests where diesel aerosol was passed through a TD set to 300 oC

.................................................................................................................................. 158

Figure 6-4. Count median diameter of particles (derived from a particle number size

distribution) for all fourteen fuel types. ................................................................... 159

Figure 6-5. Brake-specific particle phase (top panel) and vapour phase (bottom panel) PAH

emissions for the 7 fuel types where chemical analysis was performed. Error bars denote ±

one standard error of the mean................................................................................. 160

Figure 6-6. ROS concentrations (nmol/mg) for the 6 fuel types where a fluorescence signal

was obtained............................................................................................................. 162

Figure 6-7. A correlation between ROS concentrations and V_ORG for particles . 163

Figure 6-8. A graph showing the relationship between the heated particle surface area of

DPM, and V_ORG for all fuel types investigated. .................................................. 164

Figure 7-1. Figure 7-1. Typical engine exhaust size distribution both mass and number

weightings are shown ............................................................................................... 176

Figure 7-2. Particle number size distributions (corrected for dilution) for all fuel types tested

(includes ethanol fumigated diesel with different percentages of ethanol used (10, 20, 30%)

and three biodiesel feedstocks) ................................................................................ 179

Figure 7-3. PM2.5 mass emissions and emissions of organic matter from an engine run at

intermediate speed (1500 rpm) using various fuels ................................................. 180

xviii

Figure 7-4. Dependence between oxidative potential and organic content of particles. A line

of linear fit, with R2= 0.163884, is presented as well. ............................................ 181

Figure 7-5. Average mass spectra for neat diesel, E30 and B100 soy bean biodiesel at 50%

load. .......................................................................................................................... 184

Figure 7-6. : Correlation between oxidative potential, measured as the ROS concentration,

and f44 used as a marker for the content of oxygenated organic fraction ............... 186

Figure 8-1. Schematic of the experimental facility .................................................. 199

Figure 8-2a p-V indicator diagrams of fossil diesel and biodiesels at 1500 rpm, full load 203

Figure 8-2b. p-V indicator diagrams of fossil diesel and biodiesels at 2000 rpm, full load

.................................................................................................................................. 203

Figure 8-2d. p-θ indicator diagrams of fossil diesel and biodiesels at 1500 rpm, full load

.................................................................................................................................. 203

Figure 8-2d. p-θ indicator diagrams of fossil diesel and biodiesels at 2000 rpm, full load

.................................................................................................................................. 203

Figure 8-3a. Indicated mean of effective pressure of fossil diesel and biodiesels at 2000 rpm,

full load .................................................................................................................... 204

Figure 8-3b. CoV of IMEP of fossil diesel and biodiesels at 2000 rpm, full load. 205

Figure 8-4a. NHRR at 1500 rpm, 25% of full load ................................................. 206

Figure 8-4b. NHRR at 1500 rpm, full load .............................................................. 206

Figure 8-4c. NHRR at 2000 rpm, 25% of full load ................................................. 206

Figure 8-4d. NHRR at 2000 rpm, full load .............................................................. 206

Figure 8-5a. ISNOx of fossil diesel and biodiesels at 2000 rpm ............................. 208

Figure 8-5b. ISNOx /ISFC trade off, at 2000 rpm ................................................... 208

Figure 8-6a. Total particle number concentrations of fossil diesel and biodiesels at 1500 rpm

.................................................................................................................................. 210

xix

Figure 8-6b. Total particle number concentrations of fossil diesel and biodiesels at 2000 rpm

.................................................................................................................................. 210

Figure 8-7a. Particle size concentrations of fossil diesel and biodiesels at 1500 rpm, 25% of

full load .................................................................................................................... 211

Figure 8-7b. Particle size concentrations of fossil diesel and biodiesels at 2000 rpm, full

load. .......................................................................................................................... 211

Figure 8-7c . Particle size concentrations of fossil diesel and biodiesels at 2000 rpm, 25% of

full load .................................................................................................................... 211

Figure 8-7d. Particle size concentrations of fossil diesel and biodiesels at 2000 rpm, full load

.................................................................................................................................. 212

Figure 8-8a. . Indicated specific ROS of fossil diesel and biodiesels at 1500 rpm, 25% of full

load ........................................................................................................................... 213

Figure 8-8b. Indicated specific ROS of fossil diesel and biodiesels at 1500 rpm, full load

.................................................................................................................................. 213

xx

Acknowledgments

I would like to acknowledge and sincerely thank the following people and organisations who have

made this research possible:

My principal supervisor Prof. Zoran Ristovski for his guidance and unwavering enthusiasm

that kept me constantly engaged with this project. Zoran, thank you for being such a great

mentor and friend.

My associate supervisor Prof. Steven Bottle for his valuable contribution and continuous

support

My associate supervisor Dr. Branka Miljevic for her valuable mentoring and encouragement

Kathryn Fairfull-Smith for providing me with the probe whenever I needed it for my

measurements. I also thank Kathryn for her assistance and persistent faith in this project.

Queensland University of Technology for awarding me with the Post Research Graduate

(QUTPRA) scholarship. It was an honour to be a recipient of this scholarship.

My friends and colleagues in the International Laboratory for Air Quality and Health (ILAQH).

Bottle research group- thank you for reminding me how beautiful it is to be a chemist

CIMO Research Fellowships Program for awarding me with a travelling grand. I would like to

use this opportunity to express my deepest gratitude for this opportunity.

The Aerosol Physics research group from Tampere University of Technology for the

stimulative working environment and unique learning experience

On a personal level, I’d also like to extend my gratitude to

Families Osterman, Sundac and Stojanovic

Senad and Branka for all their help

To my dear friends back in Serbia- I feel truly blessed to be sheltered by your love and

loyalty

To all my friends here in Australia- You made this journey easier and far more pleasant

To my family for all their love, support and smiles- Thank you for your persistent faith in me

To my brother Branko without whom everything would be impossible. Thank you for being

my best friend and companion

Finally, I would like to thank my grandparents Sofka and Lepoje, who taught me to seek

truth and excellence without demanding it. I dedicate this thesis to you…

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ABBREVIATIONS

AAPH – 2,2’-azo-bis-(2-amidinopropane) dihydrochloride

3AP – 3-amino-2,2,5,5,-tetramethyl-1-pyrrolidinyloxy

ATP – adenosine triphosphate

BPEAnit – BPEA-nitroxide or 9,10-bis(phenylethynyl)anthracene-nitroxide

DCFH – 2’,7’– dichlorodihydrofluorescein

DCFH-DA – 2’,7’– dichlorodihydrofluorescein diacetate

DEP – diesel exhaust particles

DHR-6G – dihydrorhodamine–6G

DMPO – 5,5-dimethyl-1-pyrroline-N-oxide

DMSO – dimethyl sulphoxide

DNA – deoxyribonucleic acid

DTNB – 5,5’-dithiobis-2-nitrobenzoic acid

DTT – dithiothreitol

EPR – electron paramagnetic resonance

ETS – environmental tobacco smoke

GC-MS – gas chromatography-mass spectrometry

GM-CSF – granulocyte-macrophage colony-stimulating factor

GSH – glutathione

GSSG – glutathione disulfide

GST – glutathione-S-transferase

HC – hydrocarbons

HPLC – high performance liquid chromatography

IL – interleukin

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LC-MS – liquid cromatography-mass spectrometry

MAPK – mitogen-activated protein kinase

MS – mainstream smoke

NAD(P)H – nicotinamide adenine dinucleotide (phosphate)

NDA – naphthalenedicarboxaldehyde

NFκB – nuclear factor κB

NOx – oxides of nitrogen

NQO1 – NADPH quinine oxidoreductase

OH-1 – heme oxygenase-1

8-oxodG – 8-oxo-7,8-dihydro-2′-deoxyguanosine

Q – quinone

QH. – semiquinone

QH2 – hydroquinone

QUT – Queensland University of Technology

PM – particulate matter

POHPAA – p-hydroxyphenylacetic acid

ROS – reactive oxygen species

SOA – secondary organic aerosol

SOD – superoxide dismutase

SS – sidestream smoke

TNF-α – tumor necrosis factor α

TPO – 2,2,6,6- tetramethyl-piperidinoxyl

VOC – volatile organic compounds

WHO – World Health Organisation

1

Chapter 1

INTRODUCTION

1.1. Description of scientific problem investigated

Identification of the PM properties that are the most relevant for promoting adverse

health effects is crucial not only for our mechanistic understanding but also for the

implementation of strategies for improving air quality. Despite the availability of a huge

body of research, the underlying toxicological mechanisms by which particles induce

adverse health effects are not yet entirely understood. Recently, it has become evident that

those particles have the ability to generate free radicals and related reactive oxygen species

(ROS). These species are responsible for driving oxidative stress at sites of deposition and


concentrations, cell death.

ROS is a collective term that includes oxygen-centered and related free radicals, ions

and molecules. Key ROS involve ions such as superoxide and peroxynitrite and molecules

such as hydrogen peroxide and organic peroxides. Free radicals may also play a role in

generating ROS and these include hydroxyl, hydroperoxyl and organic peroxyl radicals.

Most of the attention in the literature has been focused on the formation of ROS in

situ after cell exposure to fine and ultrafine particles. In addition to the production of ROS

within cells that are exposed to fine and ultrafine particles, recent work has shown that ROS

are also present in the atmosphere. Atmospheric ROS can be present either in the gas phase

or bound to, or within, the particle phase. Most of the ROS in the gas phase have high

solubility and molecular diffusivity, and are mostly absorbed by the mucus in the upper

respiratory tract and therefore will not come in direct contact with the lung cells. However,

ROS that are bound to the particle phase may use the particles as a transport vector to

deliver them directly to the surface of the lung cells. As such, particle-bound ROS potentially

provides a direct source of oxidative stress and this implicates reactive particles (particles

carrying ROS) as one of the most likely causes of induced adverse health effects. The

2

hypothesis that the ROS present on particles could cause the same kind of systemic

dysfunction as ROS generated in the cells represents a fundamental issue for further

investigation.

A number of epidemiological studies have shown a higher correlation between

particles of smaller sizes especially the ultrafine ones (UFP) (<100nm) and adverse health

effects. Some of these reports have theorized that the reason for this could be because of

the higher surface area that smaller particles have for the same mass concentration. A

higher surface area can have a twofold effect. It provides a greater surface area to react

with lung tissues, but it also offers a larger area onto which toxic substances such as ROS

can condense. The combination of the two could be one of the reasons why ultrafine

particles are found in many cases to be more toxic than their larger counterparts. These

hypotheses remain insufficiently tested and we still do not have a definite explanation for

the higher toxicity of ultrafine particles. Correlation between different particle metrics,

especially size and surface area, and ROS concentration for ambient particles could give a

new insight into particle toxicity. For example a positive correlation between particle

surface area, in the ultrafine range, and ROS concentration would indicate that ROS are

mainly condensed on the surface of the ultrafine particles and do not constitute the bulk of

the particle volume. Increased understanding of such correlations should provide greater

insight into the fundamental basis of nanoparticle toxicity.

1.2 Overall aims of the study

Taking into account the research problem introduced in the previous section, the

main aim of this research project was to gain more insight into the underlying chemistry of

the reactions between PM bound ROS and nitroxides (used as scavengers of free radical

species and responders to redox-active components), identify the products arising from the

reaction of nitroxides with PM bound ROS derived from different pollution sources and

optimise the conditions required for fast and accurate quantitative detection of particle

bound ROS to enable this technique to be applied to biologically relevant test samples.

3

QUT`s profluorescent BPEA nitroxide (BPEAnit) probe was applied previously for the

assessment of the oxidative potential (OP) arising from particles generated by cigarette

smoke (Miljevic, Bottle et al. 2010), diesel exhaust(Surawski, Miljevic et al. 2009) and wood

smoke (Zhang, Jimenez et al. 2007). Following the growing interest in alternative fuel tion,

BPEAnit was used to measure the oxidative potential of various biofuels currently on the

market.

Also, one of the very important tasks in this project was to gain a better

understanding of the factors that contribute to the activity of OP and to identify a suitable

metric that describes the results in the most appropriate manner.

1.3 Specific objectives of a study

The specific objectives of the study can be summarised as follows:

Identify the products formed upon the reaction between BPEAnit and PM. For this purpose

ESIMS (electrospray ionisation mass spectrometry) and HPLC (high performance liquid

chromatography) were employed. These techniques enabled rapid characterisation of

nitroxide radicals and their products with different surrogate compounds and biodiesel PM.

Establish a correlation between the amount of particulate organic material and the amount

of ROS. For this purpose the Aerosol Mass Spectrometer (AMS) was employed which

enabled a comparison of AMS results to ROS measurements.

The involvement of organics in particulate toxicity has been established and further

research should now be able to indicate the specific class of compounds most contributing

to the oxidative potential of PM

Assessment of PM toxicity, along with organic content analysis, of biodiesel as well as

different blended fuels.

Developing improved sampling methodology. Toxicological assessment of PM toxicity

requires the conservation of the chemical and surface properties of PM during the sampling

4

process. Moreover, the technique should allow calibration of the equipment used for

sampling, so the reported results provide an accurate analysis of the problem investigated.

1.4 Account of scientific progress linking the scientific papers

This thesis contains a collection of papers in which the specific aims of the project outlined

above were addressed. These papers have been published or submitted for publication in

refereed journals.

As stated in the previous section, QUT`s profluorescent BPEAnit probe has been previously

applied for the assessment of the oxidative potential arising from particles generated by

cigarette smoke, diesel exhaust and wood smoke.

The first publication in the thesis (Chapter 3) “Application of profluorescent nitroxides for

measurements of oxidative capacity of combustion generated particles” was published in

“CI&CEQ” as a scientific paper. This paper presents a summary of the studies done using

BPEAnit for estimation of oxidative potential of PM generated by different combustion

sources. This review introduced the topic, provided an overview of the technique and the

developments made in this field by demonstrating a proof of concept regarding the

applicability of BPEAnit in detecting of particle-derived ROS. Particulate organic material has

been recognised as the fraction responsible for BPEAnit response. This review paper is a

good starting point to understand an importance of organics in particle-related toxicity and

presents a platform for a future research that is aimed to provide “a big picture” and an

understanding of the processes governing BPEAnit response.

The second paper in this thesis (Chapter 4) aimed to provide a better understanding of the

underlying chemistry leading to fluorescence generated from BPEAnit when exposed to PM.

It contains studies on the chemical characterisation of the reactions between BPEAnit and

appropriate model compounds that were chosen to present redox active species that are

likely to be found in PM. The fluorescence was monitored and the products analysed using

HPLC and LCMS. These powerful analytical tools were also used to investigate the influence

of sonication, a commonly used technique for removal of particles from filters, on a

fluorescence response. Finally, the main products responsible for the fluorescence increase

5

generated when a DMSO solution of nitroxide was exposed to biodiesel exhaust were

determined. It is entitled “The use of a nitroxide in DMSO to capture free radicals in

particulate pollution” and has been published in”European Journal of Organic Chemistry” as

a full research paper.

The volatility of particles and consequently the organic content of PMs is a very important

property that directly influences the chemical composition of aerosols and their reactivity

and related toxicity. Thermodenuders are widely used to estimate the volatile organic

component of PMs, thus providing an insight into kinetics of evaporation and condensation

within the device. The results presented in this paper indicate that the losses are higher for

smaller particles and higher temperatures. Diffusion driers are most commonly used for the

removal of gas phase, water and volatile organic phase from PM. If significant portions of

the aerosol particles are in the size range bellow 50 nm, a correction must be made for the

losses within the diffusion dryer as these losses can be as large as 50% at this size. To

establish the correction factor we have used the same mathematical model as for the TD

and applied it for the measurements conducted for the diffusion drier. The interpretation of

data when using these instruments often excludes correction factors that describe particle

losses inside these instruments. This paper is entitled “Characterisation commercially

available TD and diffusion drier for ultrafine particle losses” and is submitted to “Aerosol

Science and Technology” as a technical paper.

A fourth study was conducted in order to test the physical and chemical properties of PM

originating from the combustion of different biodiesel stocks in a compression ignition

engine. Different biofuels with various percentages in respect to petrol diesel were used.

This study provided an opportunity to look into the correlation between the physical

properties of diesel particulate matter (DPM) and oxidative potential of particles. The semi-

volatile organic component of particles was significant and it was shown that this

component correlated well with ROS emission factors. However, it was also shown that the

values for oxidative potential didn`t all exhibit a stock dependency and considerable scatter

in the relationship with volatile component was observed in certain cases. The paper is

entitled “A physico-chemical characterisation of particulate emissions from a compression

ignition engine: the influence of biodiesel stock” and has been published in “Environmental

Science and Technology” as a full research paper.

6

The results from the previous study highlighted the need to further explore the link

between PM organic content and its oxidative potential. The primary objective of the work

presented in the fifth study was to characterise emissions from a diesel engine running on

different biofuels in order to gain a better understanding of the role different organic

fractions play in biodiesel PM surface chemistry. Here, a more detailed chemical analysis of

biodiesel PM was undertaken using a compact Time of Flight Aerosol Mass Spectrometer (c-

ToF AMS). This enabled a better identification of different organic fractions that contribute

to the overall measured oxidative potential. This manuscript is entitled “The influence of

oxygenated organic aerosols (OOA) on the oxidative potential of diesel and biodiesel

particulate matter” and has been submitted to” Environmental Science and Technology” as a

full research paper.

Finally, BPEAnit was used to examine the oxidative potential of biodiesels with varying

carbon chain lengths and the degrees of saturation. The differences in the physico-chemical

properties for the biofuels and the diesel fossil fuel significantly affect the engine

combustion and emission characteristics. The presence of oxygen within the molecular

structure of the biodiesel leads to significant levels of oxygenated species with high toxicity.

In addition, the carbon chain length and the degree of unsaturation influence the biofuel

combustion chemistry and these factors are all dependent upon the feedstock used. To gain

an insight into the relationship between the molecular structure of the esters present in

different biodiesels and their respective oxidative potentials, measurements were

conducted on a modern common rail diesel engine. Tests were designed to present

emissions differences due to changes in fuel, speed and load settings, which included usage

of three blends for every biodiesel feedstock (B20, B50, B100). This paper is entitled “Engine

performance characteristics for biodiesels of different degrees of saturation and carbon

chain length” and has been published in “SAE”as a full research paper.

7

Chapter 2

LITERATURE REVIEW

2.1 Particle size distribution and composition

Air quality depends on PM and gaseous pollutants produced by a number of sources,

including road dust, combustion, condensation processes etc. Exposure to air pollutants as

well as the amount of pollutants in a volume of air is associated with adverse health effects.

Furthermore, PM and gasses (CO, SO2, O3 and N2O) also have an impact on global climate

change.

2.1.1 Background and definitions

PM is a mixture of different compounds and is derived from various sources. Consequently,

the source and physical and chemical properties of PM govern its characteristics (Englert

2004). Sources of PM include: automobiles and diesel trucks (Englert 2004), (Rogge,

Hildemann et al. 1993), road dust and traffic debris (Rogge, Hildemann et al. 1993), steam

boilers (Rogge, Hildemann et al. 1993), natural gas appliances (Rogge, Hildemann et al.

1993), natural vegetation emissions (Kroll and Seinfeld 2008); (Rogge, Hildemann et al.

1993); (Schauer, Kleeman et al. 2001), boiling/cooking operations (Rogge, Hildemann et al.

1991), (Nolte, Schauer et al. 1999), (Schauer, Kleeman et al. 1999), outdoor tobacco smoke

(Rogge, Hildemann et al. 1994), (Kavouras, Stratigakis et al. 1998), residential wood burning

fire-places (Prasad, Kant et al. 2001), and biomass burning (Dennis, Fraser et al. 2002),

(Hedberg, Kristensson et al. 2002), (Mukherji, Swain et al. 2002). Depending on the

particular area, the contribution of each source will vary.

In terms of the physical properties of PM, size plays a very important role. In addition to

this, smaller particles will stay in the atmosphere longer than the larger ones, they can be

8

transported further and can penetrate deeper into the human respiratory system. Larger

particles are usually deposited closer to their source.

Airborne particles are characterised in different modes or size ranges. Coarse particles are

particles that have diameter between 2.5 and 10 µm and are mostly generated from

mechanical processes such as grinding, breaking, etc.

Particles with a diameter less than 2.5 µm are named fine particles. Ultrafine particles have

a diameter less than 0.1 µm and largely consist of primary combustion products (from

biomass, burning, motor vehicles...)

Major components of fine particles are soot, nitrates, sulphates, condensated acids, PAHs,

n-alkanes, n-alkenoic acids, resin acids and other toxins (Hays, Geron et al. 2002). On other

hand, ultrafine particles mostly consist of organic compounds, elementary elements, metals

(from mobile source emissions) (Morawska and Zhang 2002), (Kim, Shen et al. 2002).

The size distribution of particles in the urban atmosphere is commonly presented with three

modes: nucleation (or nuclei) mode, accumulation mode and coarse mode (see Figure 1

(Hinds 2002)). Particles classified within nucleation mode have diameters less than 0.1 µm

(even smaller- 0.05 µm) and are formed by rapid nucleation of low vapour pressure

compounds (mainly produced by combustion) and from chemical conversion of gasses to

particles in the atmosphere. As they cannot exist for a very long period of time, they grow

into larger particles with diameters within the range 0.1-2 µm, known as the accumulation

mode. The accumulation mode particles are formed by coagulation of particles from the

nucleation mode and by condensation onto existing particles and can remain suspended in

the atmosphere and are not readily removed by rain. Particles in the coarse mode have

diameters larger than 2 µm and are generally formed by break-up of larger matter and

include particles from construction, wind-blown dust and soil and sea spray.

There is another particle size definition which is very important for the classification of

ambient PM in terms of air quality standards and it includes PM10 and PM2.5 which are size

fractions with an aerodynamic diameter smaller than 10 and 2.5 µm, respectively. The

above mentioned particle size definition is often used in studies related to the health effects

of PM. PM2.5 are named the fine particulate matter while those with bigger diameter are

9

called coarse particles. These size fractions are measured as mass concentration. Ultrafine

particles are a subset of PM2.5

Figure 1. Typical engine exhaust size distribution both mass and

number weightings are shown

The aspect of particle size that is currently attracting the greatest attention is the influence

of fine and ultrafine particles (including nanoparticles) on human health.

10

2.2 Combustion generated aerosol

2.2.1 Combustion

Combustion is among the major sources of PM in the urban atmosphere and it is affecting

both the indoor and outdoor air quality. Combustion or burning is the sequence of

exothermic chemical reactions between the fuel and an oxidant and the reaction is followed

by the production of heat and the conversion of chemical species. Fuels of interest usually

include organic compounds (mainly hydrocarbons) in the gas, liquid or solid phase. The most

common oxidant is atmospheric oxygen.

Combustion reactions can be complete or incomplete, although it is very difficult, almost

impossible, to achieve complete combustion in reality. Actual combustion reactions come to

equilibrium, where many other species can be present, aside from CO2 and H2O, which are

the sole products arising from the complete combustion of hydrocarbons. The minor and

major products can be present in various amounts and usually involve carbon monoxide,

pure carbon, soot or ash etc.

Also, as atmospheric air consists of 78% of nitrogen, any combustion will create several

forms of nitrogen oxides. Nitrogen does not take part in combustion, but at high

temperatures it will be converted to NOx to some extent, usually between 1% and 0.002%.

As mentioned before, when hydrocarbons are burned in oxygen, the complete combustion

reaction will only yield CO2 and H2O. Generally, when elements are burned the products are

mainly common oxides, so carbon will give CO2, nitrogen will yield nitrogen oxide, sulphur

will yield SO2.

Combustion is not necessarily completed to the full extent possible and this can be

temperature dependent. Incomplete combustion occurs when insufficient oxygen is

present, so the fuel does not react completely to produce CO2 and H2O. Apart from CO2,

H2O, SO2 and NOx, which are expected products of combustion, incomplete combustion also

results in the formation of a great number of more complex compounds, present both in the

gaseous phase and as particulates.

11

For most fuels, such as diesel, coal or wood, pyrolysis will occur before combustion.

Moreover as a part of incomplete combustion, products of pyrolysis remain unburnt and

contaminate the smoke with PM and gasses, as well as with partially oxidised compounds.

Combustion sources are various. They can be mobile and stationary, outdoor and indoor

and they range from transport sources and industrial and power plants to open fire burning

and tobacco smoke.

Combustion in the presence of oxygen is a radical chain reaction. The initiation of this

reaction requires high energy due to specific structure of the oxygen molecule. Molecular

oxygen is present in its lowest-energy configuration, which is known as the triplet-spin state.

Here, the bond between two oxygen atoms can be described with three bonding electron

pairs and two non-bonding electrons whose spins are aligned, so the molecule has nonzero

total angular moment.

On the other hand, most fuels are in singlet state, with paired spins and zero total angular

momentum. Interaction between these two species is a “forbidden” transition according to

the quantum mechanics rules and it is required to force oxygen into spin-paired state, also

called singlet oxygen. The required energy is supplied by the heat of the combustion

process.

Combustion of hydrocarbons is thought to be initiated by the abstraction of a hydrogen

atom from the fuel which is then bonded to oxygen, forming hydroperoxide radical (HOO ∙).

These radicals form hydroperoxide which is further transformed to OH ∙ radicals. It can also

produce a cascade of other reactions that generate a variety of other radicals. These

reactive intermediates include singlet oxygen, monoatomic oxygen, hydroperoxyl and

hydroperoxyl radicals. They are short lived and that makes them impossible to isolate. It

must be pointed out that varieties of other molecules are produced as intermediates during

incomplete combustion, such as carbon monoxide (CO).

Also, the most important parameter for combustion is temperature. According to the first

law of thermodynamics, the ideal conditions for complete combustion assume adiabatic

conditions. That means that no detectable gain or loss of energy is observed during this

12

reaction and that the heat of combustion is entirely used for heating the fuel, the

combustion air or O2 and product gasses.

Adiabatic temperature for every fuel depends on several factors, such as the heating value,

the stoichiometry air to fuel ratio, the specific heat capacity of fuel and air as well as the air

and fuel inlet temperature.

The conditions found in combustion systems can have a variety of impacts on the

characteristics of the particles generated, and as a result can have an impact on the ultimate

health effects through the damage they can cause within the cells. The type of fuel, the

combustion system, and the exhaust treatment systems can all have important effects. Fuel

structure, temperature, and residence time dominate the nucleation, coagulation, and

growth of aerosol particles in high temperature systems.

13

2.3 Nucleation and condensation

After they are emitted from the primary combustion sources, particles are subsequently

transformed under the influence of a number of atmospheric processes. In fact,

atmospheric processes both affect the dynamics of their behaviour in the atmosphere and

influence their physical characteristics. These atmospheric processes include nucleation of

gaseous precursors, and/or their condensation onto pre-existing particles, gas-particle

partitioning of primary semi-volatile PM with atmospheric dilution and further secondary

particle formation by means of photochemical reactions. Among these, nucleation and

condensation are the dominant factors and they control the dynamics of the emitted

particles. These are competing processes and depending on the available pre-existing

surface area and the dilution rate one of them is likely to be dominant.

Almost immediately after being emitted from the combustion source, a complex mixture of

gaseous vapours (containing semi-volatile and volatile compounds) and particulate matter

goes through a dilution phase. During the dilution phase, this mixture is rapidly cooled.

Then, it reaches super-saturation for the low-volatility gaseous compounds in the exhaust

region . New particles are formed by nucleation of gaseous vapours and/or condensation

onto pre-existing particles (Seinfeld and Pandis 1998).

As mentioned above, depending on the availability of pre-existing surface area, one of these

processes will dominate. So, if a low concentration of aerosols is present, the nucleation

process will be dominant, which is followed by the growth of newborn particles (Kulmala,

Pirjola et al. 2000).

On the other hand, high PM concentration will favour condensation of the vapours onto

pre-existing particles (Kerminen, Pirjola et al. 2001). For example, new particle formation is

not very probable in polluted environments. Due to the high surface areas present from

existing pollution, vapours of low volatility will condense onto pre-existing particles (Alam,

Shi et al. 2003).

As an example of the above, measurements have been made on the emissions from the

vehicles retrofitted with diesel particulate filters and the formation of nuclei mode particles

was observed.

14

As the usage of these filters is followed by a significant decrease in particle number, the

nucleation process will then occur. It is also observed that the overall reduction of total PM

mass emission rates leads to a reduction of surface area which will further facilitate

formation of new particles from organic vapours under certain conditions, mainly

temperature and dilution rate.

Moreover, it has been reported that nuclei mode particles can be formed from sulphates,

products of oxidation of SO2, over the oxidation catalysts. In their dynamometer study,

Grose and his co-workers (Grose, Sakurai et al. 2006) report nuclei mode particle formation

from sulphates and organic vapours in the case of vehicles equipped with emission control

devices.

Near freeways, particles formed in the nucleation process are mainly in the size range below

30nm, and they grow gradually when moving away from the freeway, through processes of

coagulation and condensation (Zhu, Hinds et al. 2002), (Ntziachristos, Ning et al. 2007).

The nucleation process involves binary (such as sulphuric acid and water) and ternary (such

as H2SO4, NH3 and H2O) formation mechanisms. The binary process is able to predict the

nucleation rates only at some extreme conditions of low temperatures, high relative

humidities, small pre-existing aerosol concentrations and at high sulphuric acid

concentrations.

The ternary nucleation model of H2SO4, NH3 and H2O gives significantly higher nucleation

rates and thus predicts nucleation under typical tropospheric sulphuric acid (105 - 107 cm-3)

and ammonia (a few p.p.t) concentrations. Although they use different thermodynamical

data (vapour pressures, surface tension) both models are in reasonable agreement showing

for example, the importance of sulphuric acid molecules in the nucleation process and

effect of ammonia (Kulmala, Pirjola et al. 2000).

It is assumed that organic vapours are not nucleating agents, but can participate in the

process of particle growth (Kulmala, Vehkamäki et al. 2004). Some studies indicate that ions

present in the exhaust can act as stabilisers in the process of nucleation (Yu and Turco

2001); (Enghoff and Svensmark 2008) but they do not act as nucleating agents as their

concentration is too low in the diesel exhaust (Ma, Jung et al. 2008). In Fig.2 it is illustrated

15

how these processes of nucleation, condensation and adsorption influence the behaviour of

exhaust particles.

Finally, Charron and Harrison (Charron and Harrison 2003) have investigated the evolution

of particle size distributions near a busy road. Their results indicate that in the early

morning, when pre-existing particle surface area was low, between 300 and 500 µm2/cm3,

vapours will favour new particle formation through nucleation and they will grow to

detectible sizes, which is contrary to the process that is happening later during the daytime,

when condensation of vapours onto pre-existing particles dominates. During the daytime

the surface area increased to 800 to 1100 µm2/cm3.

Figure 2. Illustration of the fate of exhaust particles in the atmosphere and how the

processes of nucleation, condensation, and adsorption affect the formation, dispersion

and deposition of exhaust aerosol

2.3.1 Role of dulution process

As previously stated above, dilution affects the behaviour of particles, influences their

dynamics and alters their physical and chemical characteristics dramatically. Consequently,

dilution may change their toxic properties and influence their role on population exposures

16

and public health. Following their emission from mobile sources, particles disperse into

atmospheric background in two distinctive stages:

tailpipe-to-road dilution by the strong turbulence generated by the traffic, lasting about 1-3

seconds and causing dilution up to factor 1000 (Morawska, Ristovski et al. 2008) and

atmospheric turbulence- induced dilution caused by the wind and atmospheric instability,

which lasts for 3-10 minutes, resulting in an additional dilution ratio of about 10 (Zhang and

Wexler 2004); (Phuleria, Sheesley et al. 2007).

Dilution will effect differently non-labile PM and semi-volatile PM. The atmospheric

concentration of non-labile PM will be changed under the influence of dilution, by

dispersion. Gaseous precursors will nucleate or condense onto pre-existing particles as the

result of dilution and cooling.

On the other hand, in the case of semi-volatile PM, atmospheric concentrations will be

changed as well as their physical (size distribution, concentration etc.) and chemical

properties (semi-volatile fraction). Dilution will also affect the gas-particle phase

partitioning.

The dilution ration (DR) can be calculated based on the ratio of the fleet average exhaust

carbon dioxide (CO2) concentration over an incremental ambient CO2 increase as shown in

the following equation (Zhang and Wexler 2004); (Phuleria, Sheesley et al. 2007):

17

This method has been used to determine the dilution ratio in different environments with

significant influence of vehicle emissions, including tunnel environment (Kirchstetter, Harley

et al. 1999), on freeway sites (Kurniawan and Schmidt-Ott 2006) and ambient site freeways

(Ntziachristos, Ning et al. 2007).

Process Impact

Particle coagulation

Dependent on particle size and concentration Does not affect total particle mass Cause decrease in particle number concentration and increase in particle size Increase in particle size may cause loss of mechanisms May affect diesel aerosols if dilution is delayed, not critical after typical diesel exhaust dilutions Typical time constant, τ= 1/kN0 (s) for diesel size particles, N0 = initial particle concentration (1/cm3) (Fuchs, 1964)

Adsorption / Desorption

Adsorption / desorption of volatile components will affect size and mass of measured particulate matter Availability of particulate surface will affect degree of adsorption / desorption Driven by saturation ratio

Nucleation

Homogeneous nucleation may create large numbers of new particles Nucleation rates are highly nonlinear functions of saturation ratio Heterogeneous nucleation leads to the growth of existing particles

Condensation / Evaporation Condensation / evaporation of volatile constituents will affect size and mass of measured particulate matter Affected by saturation ratio, testing conditions such as: temperature, pressure, humidity Particles formed by nucleation may grow by condensation

Table 1. Particle dynamics and behaviour

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2.3.2 Dilution effects on non-labile PM components

Nonlabile PM species are affected by dilution in terms of ambient concentrations. They

include BC (black carbon), OC (organic carbon), organic molecular traces, heavy weight

organic compounds and metals.

2.3.3 Dilution effects on semi-volatile PM components

During the first dilution stage, nucleation, condensation and coagulation are mainly

responsible for the evolution of overall particle size distribution of emissions in which semi-

volatile species play an important role. Here, the dominant particle production mechanism

is nucleation induced by sulphuric acid. This process is followed by the condensation of

organic compounds, which results in rapid growth of nuclei mode particles and relatively

slow growth of accumulation mode particles. Coagulation at this stage will contribute to the

overall size distribution, but to a lesser extent, as it is usually very slow to change the

distribution significantly. Although the first dilution stage lasts for a short period of time, it is

crucial for the activation of nuclei mode particles due to the high concentrations of

condensable species (Zhang and Wexler 2004) present.

Zhu and his co-workers (Zhu, Hinds et al. 2002) investigated size-segregated particle number

concentrations at different distances from several freeways in Los Angeles and they found

that nuclei mode particles dominated near freeways. As they moved away from the

freeway, the concentration of these particles decreased gradually and the particle

distribution shifted towards larger sizes. This is the result of the combined effects of

dilution, diffusion to available surfaces and evaporation.

Coagulation may also contribute to a lesser extent. As argued by Zhang (Zhang, Wexler et al.

2005), particle number concentration, even inside the freeway environment, are not

sufficiently high to lead to coagulation. Although limited heterogeneous coagulation of

smaller semi-volatile nano-particles on larger PM may happen during dilution, as their size

decreases their diffusivity increases progressively as they disperse away from the freeway

(Jacobson and Seinfeld 2004).

19

Ristovski et al., (2004) made further insights into the evolution of particle number

concentration and size distributions from roadway emissions to the ambient environment.

They reported mutual transformation of different modes, resulting in appereance, growth

and disappereance of these modes that lead to the maximum of total number concentration

at a particular distance fom the road.

Highly concentrated gas vapours are emitted from the engine tail-pipe and shortly

afterwards, experience supersaturation because of their rapid cooling in the atmosphere.

This causes them to nucleate and/or condense onto pre-existing particles, producing a

chemically complex aerosol. Dispersion from the roadway to the ambient environment

occurs after this stage leading to a decrease in the concentration of the gas-phase and

evaporation of some organic compounds in the exhaust or condensation of some other

compounds depending on the relative magnitude of their partial vapour pressures.

The dynamics of volatilization are more pronounced for smaller particles of the UFP range

(i.e <20 nm), because a higher vapour pressure is required to keep them from volatilizing

compared to larger particles due to the “Kelvin effect“(Hinds 2002). The evolution of

particle size distribution and number concentration is thus accompanied by changes in

particle chemical composition, since the partitioning of semi-volatile species may change

dramatically with changing the dilution ratio to maintain gas-particle phase equilibrium

(Hinds 2002).

A great part of primary combustion aerosols contains semi-volatile organic components. In

the atmosphere, these organic aerosols may experience gas-particle partitioning, depending

on their concentration, meteorological conditions, ambient concentration of their vapour

and PM phases and the degree of dilution (Pankow 1987). It is established that gas-particle

partitioning may occur via absorption into organic solution and adsorption onto soot and

mineral surfaces. Depending on the amount and type of each sorptive material, one of these

pathways will be dominant. For ambient aerosols, absorption into organic solutions will

present the central mechanism of the process described above.

Emissions from various combustion sources will contain complex mixtures of elemental (EC)

and organic carbon (OC). Their ratio will vary in the case of different sources or combustion

20

conditions. For example, wood smoke and exhaust from noncatalytic converter petrol

vehicles are dominated by organic material, while emissions from diesel engines are

generally dominated by EC. Moreover, adsorption can occur on the surface of EC or organic

compounds present can form a solution with adsorbed organic layer. Finally, adsorptive

partitioning is expected to be the dominant partitioning mechanism in emissions from

gasoline vehicles, wood combustion, and other sources with OC/EC ratios greater than 2

(Lipsky and Robinson 2005; Lipsky and Robinson 2006).

Lipsky and Robinson(Lipsky and Robinson 2006) also argued that this partitioning process is

directly influenced by dilution. Dilution leads to reduced concentrations of both semi-

volatile and sorptive species. In that case, semi-volatile species are transferred from

particles to the gas phase to maintain equilibrium. Furthermore, as the dilution increases

gradually, temperature and concentration of these semivolatile and sorptive materials will

reach background levels and then background conditions should strongly influence the

ultimate partitioning of the emissions. This new insight into partitioning theory has to be

considered in health effect studies and toxicity studies as well, as the changes in partitioning

alter both the mass and the concentration of the aerosol.

In one extensive study, Robinson (Robinson, Donahue et al. 2007) states that the amount of

organic compounds (OA) present is dilution dependent, meaning that the fuel-based

emission factors of OA decrease with increasing dilution and decreasing concentration. As

an illustration of the above statement, Fig.3 shows a set of data measured at different levels

of dilution, extending from conventional emissions to typical atmospheric conditions. Here,

primary ogranic aerosols (POA) emission factor (EF) decreases with increasing dilution due

to evaporation of SVOCs and it can be seen that POA concentrations decrease considerably

more than in the case of dispersion alone. He presented that only a quarter of primary OA is

present in the particle phase at the level of ambient dilution conditions with

atmospherically relevant concentrations. Furthermore, according to the well-established

partitioning theory, POA levels also vary with temperature.

These results indicate that we should measure volatility distributions instead of fixed POA

EFs, due to the semivolatile character of POA. Also these results imply that the majority of

the population in urban environments is exposed to SOA (except for people living near

21

sources). Consequently, a relatively local urban emissions problem becomes regional source

of oxidised and presumably hydrophilic OA.

Figure 3: Fuel-based organic aerosol emission factor as a function of their

concentrations and dilution ratios (Robinson, Donahue et al. 2007)

Moreover, the gas-phase partitioning of the complex and dynamic mixture of vehicle

exhaust also depends on the volatility of individual organic compounds, which is closely

related to the molecular weight of the compound and the functional groups present.

22

Figure 4: Vapour pressures of organic compounds as a function of carbon number and

functionality (Jacobson, Hansson et al. 2000).

To demonstrate this important feature, Ning et al. (Ning, Polidori et al. 2008) measured

levels of PAH, hopanes and steranes (common organic tracers for vehicle emissions) in

environments with different dilution ratios: near the freeway and tunnel environment. They

showed that emission rates of these compounds are in very good agreement with previous

studies with the dilution ratios ranging from 2500 near freeway to 300 in the tunnel.

On the other hand, fuel-based emission rates of light molecular PAHs were considerably

different in these environments. Near the freeway, levels of PAHs measured were 40-50 %

lower when compared to the same in the tunnel. It indicates the likelihood of the

involvement of semi-volatile organic aerosols due to the increasing dilution ratios in

ambient environment.

These results further demonstrate the significant difficulties in assessing accurately the

overall emissions of OA in the context of public exposure.

This is one of the greatest challenges in the field of atmospheric chemistry, taking into

account all the local, seasonal and temporal variations.

23

2.4 Photochemical reactions of primary emissions and secondary organic aerosol

formation

Secondary aerosols comprise a large fraction of fine particles in urban areas. They can be

divided in two categories: inorganic and organic secondary aerosols. The processes that lead

to formation of sulphates, nitrates and ammonium, as secondary inorganic aerosols are well

understood.

Due to the complexity of organic compounds and their dynamics in the atmosphere,

secondary organic aerosols (SOA) have not been fully characterized.

Generally, SOA are formed from the photooxidation of gas-phase volatile organic

compounds (VOC) by one of the three electrophilic gasses present in trace amounts: the

hydroxyl radical (OH∙), ozone (O3) and the nitrate radical (NO3∙). These oxidizers are

produced photochemically and are active as reactants during limited times of the day.

Ozone is reactive during both the daylight and night-time hours, while OH∙ is produced in

large quantities only during daylight where it arises from the photolysis of O3.

This produces singlet-D-oxygen (which is an excited state of oxygen) that reacts with water:

O3 + hν ―› O2 + O(1D)

O(1D) + H2O ―› 2 OH∙

NO3∙ is only active during night-time hours as it photolyses readily in the presence of the

sunlight. Generally, the oxidized forms of gaseous organic compounds have lower vapour

pressures than the reduced ones.

Also, vapour pressure is dependent both on the number of carbon atoms in the molecule

and on the number of polar functional groups (Jacobson, Hansson et al. 2000).

Moreover, VOC that are capable of forming SOA have more than six carbon atoms, since the

oxidation products of organic compounds with lower carbon numbers are too volatile to

condense at ambient temperatures conditions (Hung and Wang 2006). So, high molecular

24

VOC molecules will react with photochemical oxidants (OH∙, O3) and produce low-volatility

oxidation products, such as organic acids, nitro-polycyclic aromatic hydrocarbons (nitro-

PAH) etc. (Seinfeld and Pandis 1998).

One of the more studied product group of these reactive organic gasses (ROG) oxidation is

dicarboxylic acids. These compounds are abundant in photochemical smog (Jacobson,

Hansson et al. 2000) and appear to be products of the oxidation of cyclic and aliphatic

diolefins, especially by reaction with ozone. There is strong evidence that the gaseous

precursors of these aerosols can travel big distances and photochemically produce particles

at locations very far away from the sources.

Furthermore compounds, that are products from the reaction between VOCs and oxidants,

have additional functional groups, which makes them more polar and increases their

molecular weight and thereby decreases their volatility. These compounds have sufficiently

low volatilities to condense onto pre-existing particles or to establish equilibrium between

the gas and particle phase (Odum, Hoffmann et al. 1996). When nuclei or ions are not

present, nucleation can also occur when the oxidation products with very low vapour

pressure accumulate to reach high concentrations.

A goal in using information on the formation and transport of SOA is to be able to make

models that predict the spatial distribution of particles and their chemistry, based on

knowledge of gaseous emissions, weather patterns and oxidant levels. However, predicted

OA levels from most of these models have shown persistent discrepancies with measured

data, generally underestimating SOA formation (Heald, Henze et al. 2008); (Russell 2008).

Also, primary OA are commonly recognized as non-volatile in traditional inventories and air

quality models. As stated in previous sections above and also supported by recent

laboratory experiments (Lipsky and Robinson 2006); (Robinson, Donahue et al. 2007),

increased dilution ratios to ambient conditions, can make some semi-volatile fractions in the

primary OA to participate in gas-particle partitioning process.

Finally, the evaporation of primary OA may substantially contribute to the overall gas-phase

levels of organic compounds in the atmosphere in addition to the VOCs that are emitted

directly from combustion sources (Shrivastava, Lipsky et al. 2006).

25

Taking into account that traditional SOA formation mechanism models have VOCs (such as

monoterpenes and light aromatic compounds) as dominant gas precursors of

photochemical reaction in the atmosphere (Koo, Ansari et al. 2003) Robinson and his co

workers (Robinson, Donahue et al. 2007) proposed a different model with the modified SOA

formation framework. Their model accounts for both the gas-particle partitioning of semi-

volatile OA and the oxidation of all low volatility gas-phase organic vapours to simulate the

formation of SOA in the atmosphere. As shown in the figures, SOA fraction in the revised

model showed substantially higher contribution to OA than in the traditional model,

indicating the important role of semi-volatile primary OA in the formation of SOA in the

atmosphere (Ning and Sioutas 2010).

2.5 Combustion of diesel and biodiesel

2.5.1 Physical and chemical characteristics of DPM

Diesel exhaust is a complex mixture of gaseous compounds and fine particles that are

emitted by internal combustion engine. Physical and chemical characteristics of diesel

exhaust are dependent on the type of the engine, the fuel used, operating conditions,

additives as well as the control system. DPM is a very dynamical physical and chemical

system and its composition is under the strong influence of spatial and temporal factors

(Heikkil , Virtanen et al. 2009). It has been estimated that diesel exhaust consists of about

20000 different chemical compounds (Sehlstedt 2007). These include gaseous precursors

such as sulphuric acid, SO2, SO3, H2O, low-volatile organic compounds, soot particles and

metallic ash.

26

Figure 5: An engineer’s depiction of DPM

As shown in Figure 5, the primary carbon particles that agglomerate together to form a

complex, fractal-like morphology (Eastwood 2008). Carbonaceous core of DPM acts as a

surface onto which other components like sulphates, organics and metal oxides condense.

These organic compounds are the result of the incomplete combustion of the fuel and

lubricating oil and they can be classified as heavy hydrocarbons with a high boiling point.

Lighter hydrocarbons are present as well and they are usually labelled as semi-volatile

components as they undergo partitioning between a gas and particle phase, the process

which is dependent on the level of dilution and cooling of the raw exhaust (Robinson,

Donahue et al. 2007). Metallic ash (including metal oxides) originates from a lubricating oil

while sulphate component of DPM can come from the fuel or lubricating oil. Typical size

distribution of DPM is depicted in Figure 1.

DPM usually exhibits bimodal size distribution. Nucleation mode particles range in diameter

from 0.003 to 0.03 µm (Kittelson and Watts 2002)

Nucleation mode is composed of condensed volatile compounds and comprises very little

solid material (Mayewski 2002). It is estimated that 0.1-10% of the particle mass and around

90% of the particle number is found in the nucleation mode. Despite ongoing investigations,

27

the exact composition of the organics and the nature of the formation mechanisms of

nucleation mode particles are yet to be fully understood.

Accumulation mode particles are found in the range between 0.03 and 0.5 µm and they

mainly comprise carbon agglomerates and adsorbed materials like heavy hydrocarbons,

sulphuric compounds and metallic ash. Typically, 10% of the particle number and 80-90% of

particle mass is contained in the accumulation mode (Hinds 2002).

The coarse mode consists of particles with diameters above 1 µm and they are mainly

formed by the deposition and re-entertainment of materials from the engine cylinder,

exhaust manifold and also the particulate sampling system, such as dilution tunnel

(Kittelson 1998). Around 5-20% of the total particle mass is contained this mode. Ibn

addition, coarse mode particles make no contribution to the total particle number.

The processes that govern the transformation and evolution of diesel exhaust particles

(nucleation, condensation and coagulation) are influenced by the type of the fuel, fuel

sulphur content, operating conditions, lubricating oil and additives and the exhaust

treatment followed by dilution and cooling. As mentioned before, nucleation mode particles

may dominate and contribute the most to the total number concentration. These particles

are strongly influenced by the type of the engine and the fuel used as well as by operating

conditions.

Contrary to this, accumulation mode particles are not easily altered by the variation of these

factors. Generally, it is evident that more particulate matter is produced when the engine is

run at higher load and temperature with decreased air/fuel ratio (Zielinska, Sagebiel et al.

2004).

Taking into account its complex nature, the chemical composition of diesel exhaust PM (and

PM in general) is often expressed in terms of the organic carbon/elemental carbon ratio

(OC/EC). The majority of the diesel PM mass is in the form of elemental carbon, which

presents a core onto which various organic compounds may be adsorbed. Organic

compounds in diesel PM originate from unburned fuel and lubricating oil, partial

combustion and pyrolysis products and include alkanes, cycloalkanes, alkylbenzenes and

polycyclic aromatic hydrocarbons (PAHs) and their derivatives ((Liang, Lu et al. 2005)). PAHs

28

are of special concern as they are considered to be potential human carcinogens. OC/EC

ratio varies widely with the engine operating conditions, but generally there is a higher EC

contribution in diesel PM emissions when the engine is running under higher load ((Shah,

Cocker et al. 2004; Zielinska, Sagebiel et al. 2004; Sharma, Agarwal et al. 2005)). Various

metals, like Fe, Mg, Ca, Ba, Cr, Ni, Pb, Zn, Cd, Cu, are also found in diesel PM ((Sharma,

Agarwal et al. 2005)).

2.5.2 Physical and chemical characteristics of biodiesel PM

The prospect of global warming and climate change as well as limited reserves of fossil fuel,

call for alternative solutions to meet future energy needs. Although petroleum fuels play an

important role in industrial growth, transportation and the agricultural sector, stocks of

these fuels are also decreasing and their usage also presents an environmental issue.

Today biofuels are considered to offer the long-term promise of fuel-source regenerability

and reduced climate impact. Typical biofuel representatives that are the subject of public

discussion are mainly ethanol and a number of biodiesels.

Biodiesel is a mixture of mono-alkyl esters of long-chain fatty acids, usually methyl or ethyl

esters, obtained through a transesterification process. The transesterification is done to

lower the viscosity of vegetable oil and animal fat. After removing triglycerides, the viscosity

of biodiesels is comparable to that of diesel, which subsequently results in an improved

combustion.

Biodiesels can be used in conventional diesel engines. Notably, the first diesel engine was

designed by Rudolf Diesel to run on vegetable oil. This allows biodiesel to be used in current

automotive engines as a neat fuel or blended with conventional (petroleum) diesel.

Generally, there is a consensus on the reduction of CO, HC and PM upon biodiesel

combustion (Ulbrich 2009), (Herndon, Onasch et al. 2008). This reduction is primarily

associated with low sulphur and aromatic content, biodiesel oxygen content and higher

cetane value.

However, despite the reduction in the emitted PM mass, studies found decrease of particle

size followed by an increase in particle number concentration (Agarwal, Gupta et al. 2011).

29

This is one of the drawbacks that put the biodiesel implementation into the question.

According to toxicological studies (Ristovski, Miljevic et al. 2012), smaller particles are

mainly responsible for the observed negative health effects. In addition, observed reduction

in PM mass emissions is evident and there are several theories that tend to explain this

phenomenon. Firstly, increased oxygen content in biodiesels enables a more complete

combustion and promotes the oxidation of the already promoted soot. Then, it is

speculated that soot particles from diesel and biodiesel have different structures which may

also lead to the preferred oxidation of biodiesel soot.

A typical structure of diesel soot is shown in Figure 5. The size, structure, composition as

well as the total concentration of diesel particles is affected by various factors such as

engine load and speed, combustion temperature, injection pressure, sampling conditioning

of particles. Type of the fuel used diesel engines influences the morphology of particles

generated. In the case of combustion of biodiesel or blended biodiesels, most of the studies

reported a sharp reduction of DPM. Also, presence of oxygen in the fuel is the main

contender to explain this result.

Furthermore, negative health prospects of biodiesel usage in CI engines promotes the fact

that biodiesel combustion usually produces increased levels of NOx which is a known ozone

precursor (Emissions 2002) as well as increased particle-bound organic carbon (Tzamkiozis,

Ntziachristos et al. 2011).

It has also been reported that biodiesel increases emissions of some carbonyl species.

Carbonyl species are among the most significant precursors for secondary pollutants and

vehicles are a major source of these compounds in urban air. This aspect needs to be

explored into a more detail as the results reported in the literature are conflicting and not

very clear (Hesterberg, Bunn et al. 2006), (Biswas, Verma et al. 2009), (Turns 2011).

Generally, the magnitude of pollutant emissions from diesel engines running on biodiesel is

ultimately coupled to the chemical structure of the fuel molecules. It is presumed that the

presence of oxygen within the molecular structure of methyl or ethyl esters may lead to

significant levels of very toxic formaldehyde and acetaldehyde (Lapuerta, Armas et al. 2008).

30

Also, the carbon chain length and the degree of unsaturation influence the biofuel

combustion chemistry and these are dependent on the feedstock. For example, the largest

fatty acid incorporated into soybean is linoleioc acid at the approximate concentration of

55%. Linoleic acid is a polyunsaturated fatty acid known to readily oxidise, which can lead to

higher concentrations of NOx and more soot.

Heikkila et al. (2009) have studied the effect of three different fuels (fossil diesel fuel

(EN590), rapeseed methyl ester (RME) and synthetic gas-to-liquid (GTL)) on heavy-duty

diesel engine emissions. The concentration and geometric mean diameter of non-volatile

nucleation mode cores measured with RME were substantially greater than with the other

fuels. However, the soot particle concentration and soot particle size were lowest with RME.

Suggested explanation for this was the existence of impurities such as alkali metals and

metalloids (ash forming elements) which are lacking in EN590 and in paraffinic fuels such as

GTL. These elements can contribute to the core formation in the case of RME, which is

another indication of the utter importance of fuel chemistry for the resulting emissions.

A number of studies have investigated the health impacts of biodiesel emissions. The results

to date are somewhat contradictory. Some reports indicate that biodiesel exhaust is more

toxic and less carcinogenic than diesel exhaust produced in the same engine (Bünger, Krahl

et al. 2007). However, McCormic et al., observed only modest changes in negative health

effects, while some other reports indicate increased mutagenicity (McCormick 2007).

2.6 Free radicals and their generation in human body

Free radicals are generated in the human body when oxidation occurs during aerobic

respiration. Oxygen is essential for human beings, but harmful at the same time. ROS is a

collective term that includes oxygen-centered and related free radicals, ions and molecules.

Key ROS involve ions such as superoxide and peroxynitrite and molecules such as hydrogen

peroxide and organic peroxides, as well as various forms of activated oxygen (Patil, Phatak

et al. 2010). Simple body functions, such as breathing or physical activity and other lifestyle

habits such as smoking, produce substances called free radicals. Free radicals are formed as

part of our natural metabolism but also by environmental factors, including smoking,

31

pesticides, pollution and radiation. Sometimes the body’s immune system purposefully

creates free radicals to neutralize viruses and bacteria.

Free radicals are unstable species, which can react readily with essential molecules present

in our body, including DNA, fat, cell membranes and proteins. Damaged cells may lead to

health problems such as cancer, arterial and heart disease, cataracts, diabetes, and

degenerative processes associated with ageing (Patil, Phatak et al. 2010).

When a free radical attacks a molecule, the molecule is itself turned into a free radical which

then further reacts causing a chain reaction which can ultimately result in the destruction of

a cell. Antioxidants are molecules which can safely interact with free radicals and terminate

the chain reaction before vital molecules are damaged. They act as scavengers, helping to

prevent cell and tissue damage that could lead to cellular damage and disease. Antioxidants

act in three different ways: they can lower the free radical energy, prevent free radical

generation or they can stop chain oxidation reaction and at the same time they do not

become unstable. In the Figure 5 the connection between antioxidants and free radicals is

depicted (Patil, Phatak et al. 2010).

Although there are several enzyme systems within the body that scavenge free radicals, the

principle micronutrient (vitamin) antioxidants are vitamin E, beta-carotene, and vitamin C.

Additionally selenium is sometimes included in this category. The capacity to generate

antioxidants is not only determined genetically and by sex but also by age, habits and

especially diet.

Fine and ultrafine particles may cause the production of reactive oxygen species within lung

epithelial cells, and possibly within the cells of other organs including the endothelial cells of

arteries. Free radicals may also play a role in generating ROS and these include hydroxyl,

hydroperoxyl and organic peroxyl radicals (Patil, Phatak et al. 2010).

The mechanisms of PM related adverse health effects are still incompletely understood, but

a hypothesis under investigation is that many of these effects may derive from oxidative

stress, initiated by the formation of reactive oxygen species (ROS) at the surface of and

within target cells. Cumulative epidemiological and experimental data support the

association of adverse health effects with cellular oxidative stress including the ability of PM

32

to induce pro-inflammatory effects in the nose, lung and cardiovascular system as high

levels of ROS cause a change in the redox status of the cell and its surrounding environment,


concentration, apoptosis.

Figure 6. Scheme depicting connection between antioxidants and free radicals

For example, superoxide (O2ˉ˙ ) is a very powerful oxidant and the enzyme SOD is a very

good antioxidant, so SOD will transform O2ˉ˙ into H2O2. This reaction will occur only in the

presence of coenzymes such as Cu, Zn, or vitamin E. Then, the enzyme GSH-POD will

transform hydrogen peroxide into water and oxygen (which are not oxidants). GSH-POD can

react in the presence of cysteine or some antioxidants like vitamin E or selenium.

Nevertheless, fundamental uncertainty and disagreement persists regarding the following

question: What physical and chemical properties of particles can impact health risks? What

pathophysiological mechanisms are operative? And what air quality regulations should be

adopted to deal with the health risk? (Ayres, Borm et al. 2008).

33

2.7 PM toxicity and related health effects

PM is a complex mixture of solid and liquid anthropogenic and naturally occurring particles

of various sizes and composition. Numerous epidemiological studies established the link

between exposure to PM and increasing cardiac and respiratory morbidity and mortality.

Several components of ambient air pollution particles (i.e ultrafines, organic constituents,

biological components, metals and acid sulfates) have been demonstrated to have the

capacity to affect a biological response in a cell, tissue, and living system. These same

components have been associated with an oxidative stress presented by PM (Ghio and

Cohen 2005); (Ayres, Borm et al. 2008). After being exposed to particles, oxidants are being

produced and this results in a cascade of dependent cell signalling, transcription factor

activation, mediator release, inflammation and fibrosis. Interruption of the oxidative stress

can either diminish or eliminate the biological effect of PM both in vitro and in vivo (Ayres,

Borm et al. 2008).

Induction of cellular oxidative stress and resulting activation of pro-inflammatory mediators

are considered to play a central role in the development of airway diseases like chronic

obstructive pulmonary disease (COPD) and asthma (Donaldson, Stone et al. 2003). Oxidative

stress and inflammation are also linked to the formation of DNA strand brakes and oxidative

damage by inhaled particles (Shi, Duffin et al. 2006) These mechanisms are considered to

contribute to carcinogenesis and thus can provide an explanation for the observed

epidemiological associations between PM exposure and lung cancer.

Pulmonary inflammation is characterised by the influx of phagocytes into the lung and up-

regulation of cytokines including the potent neutrophil recruiting and activating factor

interleukin-8 (IL-8). Macrophages and neutrophiles are major sources of reactive oxygen

species (ROS) within the inflamed lung upon their activation. Particle-elicited inflammation

and subsequent generation of ROS can lead to oxidative DNA damage, and the pathway is

defined as secondary genotoxicity (Shi, Duffin et al. 2006). Due to their physicochemical

properties particles can also induce oxidative DNA damage, which is known as primary

genotoxicity. Also surface associated free radicals and transition metals are considered to

play the major role within this category (Shi, Duffin et al. 2006). Among all the transition

metals, as a result of its interaction with oxygen, its tendency towards donor-acceptor

34

complex formation and its abundance in nature, iron carries out a wide range of biological

functions in cells and tissues. Iron will act as a catalyst in the reactions with molecular

oxygen, as a part of normal homeostatic function, with either a labile or reactive

coordination site available and can also generate oxidants which will present a treat to life:

Fe2+ + O2 ―› Fe3+ + O2-

Fe2+ + O2- + 2H+ ―› Fe3+ + H2O2

Fe2+ + H2O2 ―› Fe3+ + OH∙ + OH-

The introduction of solid-liquid interface, ultrafines, organic constituents, biological

components, metals, and acid sulfates can all disrupt the normal homeostasis in an exposed

host (Ghio and Cohen 2005). An association between a disruption in iron homeostasis by

PM and their biological effects in a cell, tissue, and living system could explain the observed

differential toxicity of ultrafines, fine and coarse particles (i.e. greater surface area predicts

increased metal complexation and oxidative stress).Finally, transition metals present in PM

like iron cause generation of ROS, specifically hydroxyl radicals (OH∙) via the Fenton

chemistry (Donaldson, Stone et al. 2003), (Valavanidis, Vlahoyianni et al. 2005).

However, in the study of de Kok and his co-workers (de Kok, Driece et al.) no correlations

were found between radical formation and metal or transition metal concentrations or the

interaction between PAHs and metal concentrations. It would suggest that the radical

generating capacity of PM is predominantly determined by the presence of PAH or the

concentration of components that correlate strongly with PAH content.

ROS, including OH∙, are known to cause oxidative lesions to genomic DNA such as

premutagenic adduct 8-hydroxydeoxyguanosine (8-OHdG). Higher rates of 8-OHdG are a

well accepted risk factor for the development of cancer (Wessels, Birmili et al. 2010). ROS

have also been implicated in the ability of PM to activate signalling pathways that lead to

activation of inflammatory mediators, including IL-8 (Donaldson, Stone et al. 2003).

Furthermore, hydroquinones ( 1, 4- benzenediol) and other unsubstitued and methyl-

substituted dihydrobenzenes are well known as the constituents of cigarette smoke and

they can oxidise in the air producing semiquinones and quinines (Borgerding and Klus 2005);

35

(Chouchane, Wooten et al. 2006). Also, GC-MC analysis has shown that atmospheric PM2.5,

atmospheric total suspended particles (TSP), diesel exhaust particles (DEP) and wood smoke

contain different amounts of various quinines (Cho, Stefano et al. 2004);(Chung, Lazaro et

al. 2006);(Fine, Cass et al. 2001). Quinones can also be generated within the cells as a result

of metabolic activation of polycyclic aromatic hydrocarbons (PAHs) (Bolton, Trush et al.

2000), which are common constituents of ambient PM, especially combustion- generated

PM.

Semiquinone radicals can undergo redox cycling and reduce oxygen to produce superoxide

radical (O2−). Superoxide production triggers the formation of hydrogen peroxide (H2O2),

and metal ions such as Fe2+ can react with hydrogen peroxide to produce the hydroxyl

radical (.OH) via Fenton chemistry. Biological reducing molecules (e.g., ascorbate, NAD(P)H,

glutathione) reduce the oxidized quinoid substances back to their reduced states, enabling

them to again produce the superoxide radical. The process can be repeated many times, for

as long as reducing molecules are available (Squadrito, Cueto et al. 2001). A simplified

mechanism of quinoid redox cycling is shown in Figure 6.

Figure 7. Simplified mechanism of quinoid redox cycling (QH2 – catechol) (Squadrito, Cueto

et al. 2001)

36

EPR spectra of diesel exhaust (Ross, Chedekel et al. 1982; Pan, Schmitz et al. 2004;

Valavanidis, Fiotakis et al. 2005), petrol soot (Valavanidis, Fiotakis et al. 2005), airborne fine

(Dellinger, Pryor et al. 2001) and total (Valavanidis, Fiotakis et al. 2005) particulate matter,

wood smoke (Leonard, Wang et al. 2000) and various combustion – derived soots showed

very similar spectral characteristics to those observed from cigarette PM suggesting a

quinoid redox cycling for a mechanism for the generation of reactive oxygen species by

combustion - generated PM2.5 (Squadrito, Cueto et al. 2001) broadness of the EPR signals

indicates the presence of more than one type of semiquinone, although some broadness

may come from the inhomogeneity of the sample or as a result of interaction with metal

ions also present in PM2.5. It was shown that aqueous extracts of airborne total suspended

particulate matter, vehicle exhaust (diesel and petrol) and wood smoke PM (all extracted

from filters) were able to produce superoxide anion and hydroxyl radical (Valavanidis,

Fiotakis et al. 2005) when DMPO was used as a spin- trap.

However, it should be noted that the application of different pre- treatment methods in the

different studies may affect the extent of radical formation. The most common approach is

PM extraction from filters by the use of organic or polar solvents (Fine, Cass et al. 2001);

(Waldman, Kristovich et al. 2007); (de Kok, Driece et al. 2006). In their study, Pan et al.,

(Pan, Schmitz et al. 2004) reported that the semiquinone radical species involved in quinoid

recycling cannot be extracted from diesel exhaust particles, which implies that the ROS

generating capacity of PM-containing extracts may not reflect the actual exposure to ROS

after inhalation of PM. Although the radical generating capacity established in PM extracts

may correlate well with in vitro biological activity of these extracts, such as mutagenicity

and DNA reactivity, measurement of radical formation without extraction is likely to yield a

better estimate of exposure.

Finally, Polycyclic Hydrocarbons (PAHs) are the principal pollutants from incomplete

combustion, and are of special interest due to their toxicity, carcinogenicity, and ubiquitous

presence in the environment (McCrillis, Watts et al. 1992); (Bae, Yi et al. 2002). PAHs can

originate from various combustion sources including motor vehicles, home heating, fossil

fuel combustion in energy and industrial processes (Rogge, Hildemann et al. 1993); (Park,

Wade et al. 2002) and after being emitted may be present in gaseous phase or bound to

PM. Concentration of PAHs is generally higher in smaller PM size fractions (Ning, Sioutas et

37

al. 2003); (de Kok, Hogervorst et al. 2005) which is likely to be the consequence of the fact

that PAHs are formed during the combustion processes, which are known to contribute

particularly to ambient concentrations of fine and ultrafine particles. Moreover, smaller

particles have a relatively large surface for PAH adsorption. Certain PAHs are known

suspected carcinogens and some are associated with acute and chronic health effects (Fang,

Wu et al. 2004). Several PAHs such as benzo[a]antheracene, benzo[b]fluoranthene,

benzo[j]fluoranthene, benzo[k]fluoranthene and benzo [a]pyrene, associated with PM are

indirect-acting mutagens. Benzo[a]pyrene (BaP) is known human mutagens, carcinogens

and developmental toxicants. BaP is widely used as a representative PAHs because

concentrations of individual PAHs in the urban setting are highly intercorrelated (Halek,

Nabi et al. 2008).

With regard to traffic, PAH emissions profiles vary among engine types. Petrol engines emit

the greatest amount of high molecular weight PAH, such as benzo[a]pyrene or

dibenzo[a,h]antheracene, whereas the diesel engines are the principal source of low

molecular weight PAHs (Nielsen 1996); (Rogge, Hildemann et al. 1993).

Taken together, this indicates that the measurement of the ROS-generating capacity of PM

represents a promising method to predict inflammatory and mutagenic effects of these

ubiquitous air pollutants (Wessels, Birmili et al. 2010).

2.8 Particle sampling approaches for assessing PM toxicity

Organic species are the most numerous class of chemicals, and in the atmosphere each

individual compound is generally present as a small proportion of the total amount of

organic carbon. In order to estimate toxicity and to analyse chemical composition of PM, it

is essential to have a sampling system that minimises measurement error. There are many

factors that limit sampling efficiency. For example, in remote locations, where particle

concentrations are low, a long sampling time may be necessary, on the order of days, to

collect enough sample to satisfy the detection limits of analytical methods. The long

sampling time may increase sampling artifacts and limit the information concerning

temporal resolution.

38

The most commonly used method is filter collection of ambient aerosol, followed by

laboratory analyses. Since organic compounds, including secondary organics, are associated

with fine particles (i.e. below 2.5 m aerodynamic diameter), the use of an appropriate cut-

off inlet is necessary. From the point of view of a sample size, a cyclone, which allows for

higher sampling flow, would be recommended.

Filters are more commonly used due to lower cost and higher sample volume and for

reasons of practicality and because of their excellent collection efficiency. However, there

are three major drawbacks related to this approach - poor recovery of particles from the

filter (usually by solvent extraction); evaporation of semivolatile particulate-phase

compounds during the sampling (negative artefact); and adsorption of gas-phase

compounds onto the filter (positive artefact) (Turpin, Saxena et al. 2000). Sampling errors

are estimated to -80% for volatilisation-induced bias to + 50 % for adsorption-induced bias

(Benner, Eatough et al. 1991); (Turpin, Saxena et al. 2000). Furthermore, it is very common

to use high volume filter samplers (up to 1000 L min-1) to collect an adequate quantity of the

sample for further analysis. Their usage will undoubtedly cause the evaporation of

semivolatile particulate phase compounds collected on the filter.

In this offline method high impact velocities adhere insoluble PM to collection surfaces,

typically making extractions difficult. Also, collection substrates may become coated with a

brown film, which cannot be removed from the filter unless an additional solvent is used or

some physical means of removal is required (Turpin, Saxena et al. 2000).

On the other hand, extraction is needed to remove particles from the filter and prepare

them for the analysis. Usually, deionised water is used, but this implies that substances

insoluble in water will remain on the substrate. Consequently, usage of organic solvents is

required, which can be another obstacle as organic solvents used may be toxic for cells. So,

removal of these solvents follows, after which they can be analysed in vitro.

Finally, analysis of filter samples is usually conducted hours, days or weeks after sampling

which can cause aging of particles and considerable underestimation of ROS present.

Although filters are very practical and easy to use, their usage is not suitable for

toxicological analysis for all the mentioned above reasons.

39

To overcome the problems associated with filter sampling and minimise measurement

errors, new sampling techniques have been developed. Kim et al., (Kim, Jaques et al. 2001)

introduced versatile aerosol concentration system (VACES) which is capable of

simultaneously concentrating ambient particles of the coarse, fine and ultrafine size

fractions with a very high efficiency for a factor up to 30. This enables conducting in vivo and

in vitro studies.

Also, the concentration enrichment process minimizes volatilization losses in conventional

particle collectors, such as impactors and filters and concentrates ultrafine particles without

substantial changes in their compactness or denseness, as measured by the fractal

dimension analysis (Kim, Jaques et al. 2001) .

However they are not commercially available and are expensive, complicated and time-

consuming to manufacture. In addition, they have not been designed for automated use,

therefore they cannot currently be used for continuous, unattended sampling over several

days.

Liquid impingement has been found to be a very good sampling technique, which enables

particles to rapidly and directly react with the radical quencher, thus limiting possible

changes in chemical properties of particles arising during the time between sampling,

extracting and analysis. Liquid impingement is convenient when testing particle surface

reactivity, preparing samples for toxicological studies, or when ageing of particles due to

long term sampling may alter their chemical properties. Removal efficiency of impingers

with fritted nozzle tip was reported by Miljevic et al. (Miljevic, Modini et al. 2009). In this

study it is well established that removal efficiency is due to liquid impingement and filter-

like behaviour of the fritted tip. Moreover, in this approach, sonication should be employed

after sampling to remove the particles from the fritted tip into the liquid. Also, it is

highlighted that solvent capture efficiency should be estimated when doing toxicological

studies as the deposition on the glass has a deleterious effect on viability of such aerosols.

Values for the capture efficiency of the solvent alone ranged from 20 to 45%, depending on

the type and the volume of solvent. This is higher than 10%, which has been previously

reported, indicating that the increased dispersion of airstream into bubbles increases

trapping of particles by the liquid. However, for particles smaller than 0.5 µm, impingers

40

have relatively low and size dependent collection efficiency, which needs to be taken into

account when calculating the mass of particles being collected.

A potentially suitable method for particle collection would be the Particle Into Liquid

Sampler (PILS). This method was first introduced by Orsini (Orsini, Rhoads et al. 2008),

(Weber, Orsini et al. 2001). It grows submicron particles in a condensation growth chamber

and subsequently collects them using a wetted wall cyclone. A cyclone system is designed to

improve gentleness and maintain high collection efficiency. It operates due to combination

of three mechanisms: (1) condensational growth of the sample aerosol into water droplets

to coat the particles and reduce the inertia required for collection, (2) cyclonic flow to

reduce the impact velocity, and (3) a flowing water substrate into which the droplets were

collected for inline analysis. This method could be a promising methodology for a real-time

ROS monitor.

2.9 Measurement of the radical generating capacity of the particulate matter

2.9.1 In vitro studies

In vitro studies investigate cellular, biochemical and molecular mechanisms that are related

to the PM toxicity and use cultured mammalian cells (either immobilized cell lines or freshly

harvested lung cells (primary cells)). Although it is very hard to determine the specific

fundamental biochemical mechanisms that are related to the PM toxicity, toxicological

studies have demonstrated that oxidative stress is the most dominant route for exerting

toxicity by PM. They can be divided into three groups based on the severity of the cellular

damage induced:

Expression of antioxidant and drug metabolizing enzymes (protective cellular responses)

such as GST or SOD (for example (Li, Venkatesan et al. 2000)).

Expression of genes encoding these proteins as an indicator of oxidative stress, which has

been the subject of many previous studies that demonstrated increased production of these

41

proteins upon PM exposure (for example (Li, Sioutas et al. 2003), (Pandya, Solomon et al.

2002)).

Cytotoxicity assays assess cell death upon PM exposure-apoptosis (programmed cell death)

(for example by staining cellular DNA (Hetland, Cassee et al. 2004)).

Another method for examining PM toxicity is induction of DNA damage that is based on

biological indicators (Dellinger, Pryor et al. 2001), (Donaldson, Beswick et al. 1996).

Currently numerous in vitro assays for determination of different cellular responses to

oxidative stress have been developed.

2.9.2 Cell-free assays

In order to provide a rapid screening test to assess the oxidative potential of PM, several

quantitative acellular tests have been developed. Their advantage is that they are cheaper

and less time consuming and can be applied outdoors. Furthermore they do not need

ethical approval. These assays reflect the chemical properties of PM that are leading to

oxidative stress under biological condition.

The only analytical approach that permits the direct detection and quantification of radical

species is electron paramagnetic resonance (EPR). It is widely used to assess ultrafine

particles and particle-induced ROS generation. This method allows the quantification as well

as specific identification of the free radical species generated when specific spin traps or

probes are used in the combination with specific reagents. Examples of EPR methods used

in conjunction with nanoparticles and particles are the measurement of the H2O2-

dependent formation of hydroxyl radicals with the spin trap 5,5-dimethyl-1-pyrroline-N-

oxide (DMPO) (e.g. (Knaapen, Shi et al. 2002)), or the formation of superoxide anion using

the spin probe 1-hydroxy-4-phosphonooxy-2,2,6,6-tetramethylppiperidine (PP-H)

(Papageorgiou, Brown et al. 2007). In addition, Fenoglio et al. (Singh, Shi et al. 2007)

demonstrated using EPR that ultrafine particles can also quench rather than generate ROS in

cell-free environments.

42

Apart from the complexity and high price of the instrument, potential pitfall of EPR-based

measurements of ROS formation by nanoparticles may result from chemical or physical

interference with spin-trapping agents, and could be checked by the analysis of specific ROS

donor systems (e.g. xantine /xantine oxidase, H2O2/Fe) spiked with nanoparticles (Stone,

Johnston et al. 2009).

Figure 8: Simulated EPR spectrum of the H2C(OCH3) radical

A number of assays are available such as DTT, POHPAA, DSCH, DHR-6G assays as well as the

ascorbate depletion test.

However fluorescence-based assays have been most commonly used in the quantification of

PM-related ROS, primarily due to the high sensitivity of fluorescence detection. They are

based on non-fluorescent or weakly fluorescent molecules that yield fluorescent products

upon reacting with ROS.

43

2.9.2.1 DTT assay

Dithiothreitol (DTT) is the common name for a small-molecule redox reagent known as

Cleland's reagent. DTT is an unusually strong reductant, owing to its high conformational

propensity to form a six-membered ring with an internal disulfide bond.

Kumagai and his co-workers (Kumagai, Koide et al. 2002) demonstrated that

phenanthraquinone acts as a catalyst for the thiol-mediated reduction of O2. This leads to

the generation of reactive oxygen species (such as superoxide) and thiol oxidation. The

consumption of DTT is dependent on the ability of given sample to accept electrons from

DTT and transfer them to oxygen. When a reaction is monitored under conditions of excess

DTT, the rate of DTT consumption is proportional to the concentration of the catalytically

active redox-active species in the sample (Fig. 8). In addition, Cho et al. (Cho, Sioutas et al.

2005) applied this method to diesel exhaust PM. The DTT consumption was determined by

measuring the non-reacted DTT with the thiol reagent, 5,5’-dithiobis-2-nitrobenzoic acid

(DTNB), to give 5-mercapto-2-nitrobenzoic acid which is then detected by absorbance

spectroscopy. They also observed that limited number of species is prone to this reaction,

such as PAH- quinines which can act as a redox catalyst. Consequently, transition metal ions

(such as Fe or Cu ions) are not active in DTT reactions.

Another important issue was to calculate the rate of consumption, the DTT loss over time.

This step presents a limitation of the assay as incubation times of up to 90 min are needed

(Cho, Sioutas et al. 2005); (Li, Sioutas et al. 2003). Another drawback of this approach is the

extra step (reaction with DTNB) that needs to be applied in order to calculate DTT

consumption.

44

Figure 9: Chemical reaction between DTT and oxygen with PM as a catalyst

2.9.2.2. Ascorbate- Dihydroxybenzoate Based Redox Activity

This assay is based on the reaction between reduced metals such as CuI and FeII and

hydrogen peroxide to generate the highly reactive OH· radical. Then, hydroxyl radical will

react with a substrate such as salicylic acid to form several dihydroxy benzoate isomers,

mostly the 2,3-and 2,5 dihydrobenzoates (DHBAs) (Ayres, Borm et al. 2008). These

compounds are quantified using HPLC technique.

45

Figure 10: Chemical basis of the ascorbate-dihydroxybenzoate (DHBA) asaay

2.9.2.3 POHPAA assay

Hasson and Paulson (2003) have used p-hydroxyphenylacetic acid (POHPAA) with

horseradish peroxidise enzyme as a catalyst to detect hydroperoxides in gas and particle

phase of urban air, where the generation of a fluorescent product was a measure of the

hydroperoxides present in urban aerosol (Hasson and Paulson 2003).

2.9.2.4 DCFH assay

The use of 2`, 7`- dichlorofluorescin diacetate (DCFH-DA)was first described as a

fluorometric assay of hydrogen peroxide in the presence of peroxidise by Keston and

Brandt. (Brandt and Keston 1965). Today, DCFH-DA is widely used as a marker for oxidative

stress. It has been suggested that this compound would be a good indicator of the overall

oxidative status of the cell (Wang and Joseph 1999). DCFH-DA is a non-polar, hydrophobic

compound. It is enzymatically hydrolysed (or in the presence of NaOH) to nonfluorescent

46

DCFH and in the presence of reactive oxygen species , DCFH is then rapidly oxidised to highly

fluorescent 2`, 7`- dichlorofluorescin, whose fluorescence can be measured at 520-535 nm

(Figure 10).

Foucaud et al., (Foucaud, Wilson et al. 2007) investigated behaviour of DCFH-DA in the

presence of horseradish peroxidise (HRP) and bovine serum albumin (BSA) and compared

their results to the ones from flow cytometry. They reported that DCFH can be oxidised by

HRP alone, even at lowest concentrations used. In addition, HRP catalyses the reaction

between DCFH and H2O2. The initiator of the reaction with HRP could be any peroxide

substrate for HRP because the superoxide radical and consequently H2O2 are an avoidable

consequence of DCFH oxidation (Bonini, Rota et al. 2006). Furthermore, the study of

Foucaud (Foucaud, Wilson et al. 2007) confirmed that the presence of peroxidise was

essential for DCFH to be oxidised by ultrafine particles. Also, defined conditions implied the

necessity of the use of small quantities of HRP (0.1 u/ml) and 0.1 % BSA in the reaction

mixture to avoid agglomeration during the measurement. It should be noted however that

BSA will prevent agglomeration and not aggregation and that this stabilising effect of BSA is

due to the adsorption of BSA on the surface of particles (Valstar, Almgren et al. 2000)

Moreover, Ohashi and his co-workers reported that oxidation of DCFH is not only related to

the ROS content present but also to the heme content of the cells.

Venkatachari et al.,(Venkatachari, Hopke et al. 2005); (Venkatachari, Hopke et al. 2007),

followed by many other researchers, convert the measured fluorescence intensities into

equivalent hydrogen peroxide concentrations and then use these data as indicators of ROS

reactivity, by calibration using H2O2 standard. They report results as nmol of H2O2/m3 of air

sampled or nM of H2O2/m3.

However, DCFH is prone to autooxidation and thus brings into question the suitability of this

assay.

47

Figure 11: Hydrolysis of DCFH-DA and ROS-induced oxidation of DCFH

2.9.2.5 DHR-6G assay

Ou and Huang (Ou and Huang 2006) used this compound to investigate ROS quantity in

cigarette smoke. The proposed mechanism of action is shown in Figure 11. Here, DHR-6G

reacts with two radical species to form highly fluorescent rhodamine 6G. The amount of

ROS present was quantified using the calibration curve based on the fluorescence intensities

of known concentrations of rhodamine- 6G.

However, this compound is labelled as air-sensitive and photo-sensitive. This implies that in

the presence of either oxygen or light, significant background fluorescence can be

produced, which is the limitation of this approach.

48

Figure 12: Chemical basis of DHR-6G assay

2.10 Nitroxides as spin-trapping agents

Nitroxides are stable free radical compounds with the general formula RR`(NO˙). Their

stability is due to the presence of the strong delocalisation of the unpaired electron

between nitrogen and oxygen atoms. Another important characteristic is the kinetic stability

of the nitroxide group which is based on steric hindrance via bulky groups (usually methyl

groups) on the adjacent (α) carbon atoms.

They are very effective scavengers of other more reactive free radicals and they trap

carbon-, sulphur-, and phosphorus- centered radicals nearly at diffusion controlled rates (~

107-109 M-1s-1) to form stable products (alkoxyamines) (Beckwith, Bowry et al. 1992),

(Busfield, Grice et al. 1995), (Busfield, Heiland et al. 1995). On the other hand, they do not

trap oxygen-centered radicals to form such adducts, although they are involved in their

decay through reactions of oxidation and reduction (Krishna, Russo et al. 1996), (Takeshita,

Saito et al. 2002), (Jia, Tang et al. 2009). They can be reduced to hydroxylamine or oxidised

to oxoammonium cation, thus they can act both as reducing agents and as oxidants.

It is reported that nitroxides also scavenge nitrogen dioxide (Goldstein, Merenyi et al. 2002),

hydroxyl radicals, peroxyl radicals (Goldstein and Samuni 2007) and carbonate radicals. They

also possess an ability to oxidize transition metals such as Cu+ an Fe2+ through inhibition of

Fenton reactions that are leading to the ROS generation.

49

2.10.1 Profluorescent nitroxides

Nitroxides are well-known as effective quenchers of excited states of fluorescent moieties.

The proposed mechanism is an electron exchange interaction between the ground state of

nitroxide and the excited state of the fluorophore leading to intersystem crossing to the

triplet state, or internal conversion to the ground state of the fluorophore (Blough and

Simpson 1988), (Green, Simpson et al. 1990). In addition to this, in the presence of nitroxide

moiety, fluorophores exhibit strongly suppressed fluorescence emission although the exact

mechanism of fluorescence quenching is not completely understood and is still the subject

of further investigation.

Several nitroxides containing covalently linked fluorescence structures have been

synthesized (Fairfull, Blinco et al. 2008). These molecules react with radicals, leading either

to reduction of the nitroxides to the hydroxylamines or oxidation to oxoammonium cation.

Both pathways lead to the formation of a diamagnetic product (Figure 12). This eliminates

the intramolecular quenching caused by nitroxide moiety and thereby leads to a significant

increase in the fluorescence yield of a compound. In other words, covalent linkage of a

nitroxide moiety to a fluorophore efficiently quenches the excited states, which leads to

fluorescence. Fluorescence yield of a compound closely linked to a paramagnetic group can

be substantially increased by reactions that lead to a loss of paramagnetism in the centre.

Figure 13: The redox transformations between (from left to right) oxoammonium cation,

nitroxide and hydroxylamine

The paramagnetic nitroxides are known to be efficient quenchers of excited singlet states of

aromatic hydrocarbons presumably through an intramolecular electron exchange, which is

the reaction between ground-state nitroxide and excited-state compound within a collision

complex. Proximity of the paramagnetic group leads to quenching of fluorescence emission

from the fluorophore. Preferential reaction of the nitroxide with a radical leads to the

50

formation of diamagnetic product by eliminating the intramolecular quenching pathway.

Increased fluorescence results, which reflects radical/redox scavenging.

The measure of the number of radicals trapped by the nitroxides or other redox reactions

that occur is the intensity of the fluorescence emission. These nitroxides are classified as

profluorescent according to the fact that they are initially non-fluorescent but can be

transformed into a fluorescent form after a simple chemical reaction. Taking into account

the above, these molecules can serve as powerful optical sensors applicable as detectors of

free radicals and dynamic fluorescent indicators of the overall redox environment in cellular

systems (redox active agents).

Figure 14: 9-(1,1,3,3-tetramethylisoindolin-2-yloxyl-5-ethynyl)-10-(phenylethynyl)

anthracene (BPEAnit)

BPEA nitroxide is synthesised at QUT by the method of Fairfull-Smith et al., (2008) and is a

stable crystalline compound in the presence of oxygen. It contains a fluorophore (9,10-

bis(phenylethynyl)anthracene) (BPEA fluorophore) covalently linked to a 5-membered

nitroxide-containing ring. In the presence of nitroxide, fluorescence of the fluorophore is

suppressed by quenching. When the nitroxide losses spin as a consequence of radical

trapping or redox activity, this quenching effect is eliminated, which triggers the

fluorescence response (Figure 13).

51

Furthermore, it has an UV-absorption (fluorescence excitation) maximum at 430 nm, and

fluorescence emission maxima at 485 and 513 nm. The excitation and emission wavelength

of the BPEAnit are long enough to avoid overlapping with the background fluorescence

coming from optically active compounds which may be present in PM (e.g. polycyclic

aromatic hydrocarbons and their derivatives).

2.11 Application of profluorescent nitroxide for the detection of particulate

matter bound ROS

Many studies were conducted in order to gain information regarding radical species related

to PM. Flicker & Green (Flicker and Green 1998), (Flicker and Green 2001) and Bartalis et al.

(Bartalis, Chan et al. 2007), (Bartalis, Zhao et al. 2008) have used amino nitroxide 3AP to

quench carbon-centered radicals in mainstream cigarette smoke (Bartalis, Zhao et al. 2008),

(Bartalis, Chan et al. 2007), (Flicker and Green 1998; Flicker and Green 2001), and diesel

exhaust (Flicker and Green 1998).

Alaghmand & Blough (Alaghmand and Blough 2007) applied a similar approach to measure

production of hydroxyl radicals by a wide range of coarse PM types. The basis of their

approach is formation of methyl radical from the reaction between DMSO and hydroxyl

radical, which is then trapped with 3AP. Potential limitation, is that highly reactive radicals,

such as hydroxyl radicals may also react partially with the fluorophore, resulting in

alteration or destruction of the fluorophore.

During the past seven years numerous nitroxides have been synthesized at QUT. These

nitroxides possess fluorophores covalently bound within the structure, whereas most of the

other nitroxide-fluorophore adducts used by other researchers have labile linkages that are

prone to hydrolysis and resulting separation of the nitroxide from the fluorophore. This

important feature makes the QUT probes superior to previously synthesized nitroxides

because of their enhanced chemical and thermal stability. All these nitroxide containing

fluorophores display substantial fluorescence suppression. Also, they have the same

excitation and emision maxima as the fluorophore itself.

52

Some of these nitroxides, synthesized at QUT are shown in the Figure 14:

2) 3)

Figure 15: Structures of some of the profluorescent nitroxides synthesised at QUT. In

these examples five membered nitroxide ring is covalently fused to: 1) 9,10-

bis(phenylethynyl)anthracene (BPEA); 2)9,10-diphenylanthracene and 3) phenanthrene.

2.12 Oxidative potential of ambient PM and redox properties of DEP and biodiesel PM

As previously stated, the induction of oxidative stress by PM is considered to play a major

role in producing adverse health effects on humans. The risk posed by particles is a result of

several factors and cannot be explained by a single parameter (Bouwmeester, Lynch et al.

2011). However, by measuring oxidative potential (OP) of PM an information on the

hazardness can be obtained and this can be used as a promising and integrative metric for

health assessment purposes (Borm, Kelly et al. 2007). Also, the relationship between

particle properties (size, surface area and composition) and measured OP of PM is yet to be

fully understood. A better understanding how the toxicity of PM varies with its chemical

characteristics is vital in designing more effective emission control strategies.

53

Li et al., (Li, Sioutas et al. 2003) explored the relationship between different oxidative

potentials of particles from coarse, fine and ultrafine range with their physical

characterisation. UFPs proved to show the highest levels of ROS on a microgram basis. This

was in accordance with the uptake in macrophages and epithelial cells and their ability to

cause oxidative stress. Also, UFPs had the greatest percentage of organic carbon, followed

by fine particles and finally coarse particles.

Oxidative potential of atmospheric PMs was documented in numerous studies ((Hung and

Wang 2001), (Yungang, Philip et al. 2011), (Mudway, Stenfors et al. 2004; Mudway, Duggan

et al. 2005; McCormick 2007). Mesured OP depended on the size distribution and number

concentration of these particles as well as on their composition and the amount of metals

present ((McCormick 2007), (Yungang, Philip et al. 2011).

The principal source of PM emissions in urban areas is from combustion, principally from

motor vehicles (Kim, Shen et al. 2002). Motor vehicles are therefore the source of primary

PMs and reactive gas precursors that through the atmospheric processesing produce

secondary PMs. Other sources, like wood burning, cooking etc., contribute to higher

atmospheric PM concentration, but to a lesser extent.

Both occuopational and environmental exposure to diesel PM can be considerable (Ma and

Ma, 2002) and various studies indicate DEP can induce wide range of toxicities (Bunger etal.,

2000, Solomon abd Balues 2003., ).

Characterisation of vehicular exhaust has been done by many researchers and an attempt

has been made to relate PM chemistry to the oxidative potential of particles in question.

Gekker et al., (2006) investigated physicochemical and redox characteristics of PM emitted

from gasoline and diesel passenger cars. This study included various engine configurations,

fuel types and after-treatment technologies. For the estimation of OP, DTT was used. The

general conclusion from this work was that the reduction in PM mass and emission factors

could not be correlated to the decreased redox potential, while redox chemistry was in

correlation with low volatile PAHs, trace metals (Li, Be, Ni, Zn), elemental and organic

carbon.

54

Also, usage of diesel particulate filters (DPF) reduced the emitted PM mass 25 times, while

PM redox potential was reduced for 8 times. Overall, reported OP per mass of PM was

increased three times. Still the vehicle equipped with DPF emitted the lowest level of ROS,

one eighth of that for conventional diesel and 30% less than for the gasoline vehicle.

In another study performed by Cheung et al., (Sioutas 2009), redox potential was tested for

three different vehicles in five different configurations. Vehicles were fueled with petro

diesel and biodiesel, equipped with DPF and two types of oxidative catalysts. As expected,

the lowest overall PM emissions were observed for the DPF equipped diesel vehicle,

followed by gasoline vehicle. In both cases, low OP was reported, which decreased by 98%

in the case of DPF equipped diesel car.

The study also showed that DTT consumption correlated well with carbonaceous species

such as water soluble organic carbon (WSOC), water insoluble organic carbon (WISOC) and

OC. No correlation was found with inorganic ions (Cl-, NO3-, SO4

2-, Na+, NH4+etc.). Generally,

diesel and biodiesel exhaust released the most potent PM species in terms of their ROS

content.

As it was previously established that the presence of carbonaceous compounds in the

exhaust triggers DTT consumption, Li et al., 2009 and Mc Whinney et al., 2011, tested the

transformation of DEP upon aging in the atmosphere. Aged diesel particles had a much

higher oxidative potency while consequently lead to the elevated estimated toxicity.

Authors argued that the observed result was probably due to the interaction between

gaseous pollutants and PMs. However, the mechanisms of this were yet to be understood.

Furthermore, Surawski et al., reported OP of PMs generated by a diesel engine using

ethanol substitution. This study found that with increasing amount of fumigated ethanol in

the fuel, the PM mass is decresing and ROS concentrations incresing accordingly. The

obtained values for ROS concentrations were almost 40 times higher for E40 test than for

neat diesel. ROS concentrations exhibited an increase with decersing engine load. Suggested

explanation for increased redox potential of ethanol fumigate diesel was the occurence of

nucleation mode particles. PMs in this mode are composed of organic species and

contribute very little to the PM mass. In addition, this study showed that the toxicological

55

potential of particulate emissions is affected by operational practice and resulting

combuction.

Finally, based on the data provided in the literature so far, there are some uncertanties

about the nature of chemical moities that lead to the redox activity, ROS generation and

overall toxicity, particularly in respect to their solubility in organic solvents and water.

It is of critical importance to understand which PM fraction governs the toxicity of PMs as

this has far reaching consequences on how we regulate emissions from combustion sources,

such as diesel vehicles.

56

LITERATURE

Agarwal, A. K., T. Gupta, et al. (2011). "Particulate emissions from biodiesel vs diesel fuelled compression ignition engine." Renewable and Sustainable Energy Reviews 15(6): 3278-3300.

Alaghmand, M. and N. V. Blough (2007). "Source-dependent variation in hydroxyl radical production by airborne particulate matter." Environmental Science & Technology 41(7): 2364-2370.

Alam, A., J. P. Shi, et al. (2003). "Observations of new particle formation in urban air." Journal of Geophysical Research-Atmospheres 108(D3).

Ayres, J. G., P. Borm, et al. (2008). "Evaluating the Toxicity of Airborne Particulate Matter and Nanoparticles by Measuring Oxidative Stress Potential—A Workshop Report and Consensus Statement." Inhalation Toxicology 20(1): 75-99.

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Yu, F. Q. and R. P. Turco (2001). "From molecular clusters to nanoparticles: Role of ambient ionization in tropospheric aerosol formation." Journal of Geophysical Research-Atmospheres 106(D5): 4797-4814.

Yungang, W., K. H. Philip, et al. (2011). "Laboratory and Field Testing of an Automated Atmospheric Particle-Bound Reactive Oxygen Species Sampling-Analysis System." Journal of Toxicology 2011.

Zhang, K. M. and A. S. Wexler (2004). "Evolution of particle number distribution near roadways--Part I: analysis of aerosol dynamics and its implications for engine emission measurement." Atmospheric Environment 38(38): 6643-6653.

Zhang, K. M., A. S. Wexler, et al. (2005). "Evolution of particle number distribution near roadways. Part III: Traffic analysis and on-road size resolved particulate emission factors." Atmospheric Environment 39(22): 4155-4166.

Zhu, Y., W. C. Hinds, et al. (2002). "Study of ultrafine particles near a major highway with heavy-duty diesel traffic." Atmospheric Environment 36(27): 4323-4335.

Zielinska, B., J. Sagebiel, et al. (2004). "Phase and size distribution of polycyclic aromatic hydrocarbons in diesel and gasoline vehicle emissions." Environmental Science & Technology 38(9): 2557-2567.

68

Chapter 3

APPLICATION OF PROFLUORESCENT NITROXIDES FOR

MEASUREMENTS OF OXIDATIVE CAPACITY OF COMBUSTION

GENERATED PARTICLES

S. Stevanovic1,2, Z.D. Ristovski1, B. Miljevic1, K. E. Fairfull-Smith2, S. E. Bottle2.

1International Laboratory for Air Quality and Health, Queensland University of Technology,

GPO Box 2434, 4001, Brisbane, Australia

2ARC Centre of Excellence for Free Radical Chemistry and Biotechnology, Queensland

University of Technology, GPO Box 2434, 4001, Brisbane, Australia

S. Stevanovic, Z.D. Ristovski, B. Miljevic, K. E. Fairfull-Smith, S. E. Bottle, Application of

profluorescent nitroxides for measurement of oxidative capacity of combustion generated,

CI&CEQ 18 (4) 653−659 (2012) 653

69

STATEMENT OF JOINT AUTORSHIP

Title: Application of profluorescent nitroxides for measurement of oxidative capacity of

combustion generated

Authors: S. Stevanovic, Z.D. Ristovski, B. Miljevic, K. E. Fairfull-Smith, S. E. Bottle.

S.Stevanovic (candidate)

Wrote the manuscript.

Z.Ristovski

Assisted with the manuscript; Reviewed the manuscript

B.Miljevic

Contributed to the content of the review article and reviewed the manuscript.

K. E. Fairfull-Smith

Reviewed manuscript.

S.Bottle

Reviewed the manuscript.

70

Application of profluorescent nitroxides for measurement of oxidative capacity of

combustion generated

S. Stevanovic1,2, Z.D. Ristovski1, B. Miljevic1, K. E. Fairfull-Smith2, S. E. Bottle2





Abstract

Oxidative stress caused by generation of free radicals and related reactive oxygen species

(ROS) at the sites of deposition has been proposed as a mechanism for many of the adverse

health outcomes associated with exposure to particulate matter (PM). Recently, a new

profluorescent nitroxide molecular probe (BPEAnit) developed at QUT was applied in an

entirely novel, rapid and non-cell based assay for assessing the oxidative potential of

particles (i.e. potential of particles to induce oxidative stress). The technique was applied on

particles produced by several combustion sources, namely cigarette smoke, diesel exhaust

and wood smoke. One of the main findings from the initial studies undertaken at QUT was

that the oxidative potential per PM mass significantly varies for different combustion

sources as well as the type of fuel used and combustion conditions. However, possibly the

most important finding from our studies was that there was a strong correlation between

the organic fraction of particles and the oxidative potential measured by the PFN assay,

which clearly highlights the importance of organic species in particle-induced toxicity.

Key words: combustion particles, diesel particles (DPM), oxidative stress, reactive oxygen

species (ROS).

71

3.1 Introduction

Particulate pollution has been widely recognised as an important risk factor to human

health with $3.7 billion spent on respiratory diseases in Australia alone. Epidemiological

studies have established strong associations between exposure to ambient particulate

matter and increased respiratory and cardiovascular disease morbidity and mortality,

particularly among individuals with pre-existing cardiopulmonary diseases (Englert 2004).

Recently the International Agency for Research on Cancer (IARC), which is part of the World

Health Organization (WHO), classified diesel engine exhaust as carcinogenic to humans

(Group 1) on the 12th June 2012, based on sufficient evidence that exposure increases risk

for lung cancer. To develop methods that could help to mitigate the adverse health

outcomes induced by PM, it is important to know the PM properties and the mechanism(s)

that are responsible for PM toxicity. Identification of the PM properties that are the most

relevant for promoting adverse health effects is crucial not only for our mechanistic

understanding but also for the implementation of strategies for improving air quality.

Despite the availability of a huge body of research, the underlying toxicological mechanisms

by which particles induce adverse health effects are not yet entirely understood.

One of the important aspects of environmental sciences in the last decade was to identify

the physical and chemical characteristics of ambient PM responsible for its health effects

and within that scope, particle size, surface area and chemical components, such as metals

and certain classes of organics (e.g. quinones) have been implicated in PM-induced health

effects and more specifically, in the generation of reactive oxygen species (ROS).

ROS can be formed endogenously, by the lung tissue cells, during the phagocytic processes

initiated by the presence of PM in the lungs, or by particle-related chemical species that

have the potential to generate ROS. In addition to the particle-induced generation of ROS,

several recent studies have shown that particles may also contain ROS (so called, exogenous

ROS). As such, they present a direct cause of oxidative stress and related adverse health

effects and the hypothesis that particles contain or produce ROS is the driving force for this

research project.

It is a reasonable assumption that exogenous ROS can cause the same responses (oxidative

stress) in the cell as endogenously formed ROS. Therefore, a rapid screening assay able to

72

evaluate PM oxidative potential in terms of their inherent ROS, and therefore their ability to

cause oxidative stress, would be beneficial for gaining better understanding about the

nature of the particles most relevant for their negative health impact. Such a screen would

also provide a helpful tool in efforts to further improve air quality and protect public health.

To address this need we have developed a methodology for quantitative detection of the

oxidative capacity of airborne nanoparticles based on in-house developed profluorescent

nitroxide molecules. This methodology has been evaluated on combustion-generated

particles. Correlations between various particle properties and their oxidative capacity, as

measured by our molecular probes, will be discussed.

3.2. Methodology

Cellular responses to oxidative stress have been widely investigated using various cell

exposure assays ((Li, Venkatesan et al. 2000; Dellinger, Pryor et al. 2001; Li, Sioutas et al.

2003; Hetland, Cassee et al. 2004). However, in order to provide a rapid screening test for

the oxidative potential of PM, less time-consuming and cheaper, cell-free (or acellular)

assays are necessary.

The only analytical approach that permits the direct detection and quantification of radical

species is electron paramagnetic resonance (EPR). This method allows the quantification as

well as specific identification of the free radical species generated when specific spin traps

or probes are used in the combination with specific reagents. Apart from the complexity and

high price of the instrument, a potential pitfall of EPR-based measurements of ROS

formation by nanoparticles may result from chemical or physical interference with spin-

trapping agents, and could be checked by the analysis of specific ROS donor systems (e.g.

xanthine /xanthine oxidase, H2O2/Fe) spiked with nanoparticles (Stone, Johnston et al.

2009). Several cell-free approaches have been used to explore oxidative potential of PM in a

quantitative manner. They all have certain limitations, do not provide directly comparable

results and, to date, none of these assays has been acknowledged as the best acellular assay

and none have yet been widely adopted for investigation of potential PM toxicity.

73

A number of assays are available such as DTT(Cho, Sioutas et al. 2005), POHPAA(Hasson and

Paulson 2003), DCFH(Foucaud, Wilson et al. 2007), DHR-6G(Ou and Huang 2006) assays as

well as the ascorbate depletion test(Ayres, Borm et al. 2008).

However, DTT is reactive towards limited number of species, it requires an additional step

that may be a potential source of an experimental error and also the usage of this probe

requires an incubation time of up to 90 mins (Cho, Sioutas et al. 2005). On the other hand,

DCFH is prone to autooxidation and thus brings into question the suitability of this assay.

Also, DHR-6G is air sensitive and photo-sensitive which limits its performance as either

oxygen or light can produce significant background fluorescence

Out of all of the assays the fluorescence-based ones have been most commonly used in the

quantification of PM-related ROS, primarily due to the high sensitivity of fluorescence

detection. They are based on non-fluorescent or weakly fluorescent molecules that yield

fluorescent products upon reacting with ROS.

Nitroxides are well-known as effective quenchers of excited states of fluorescent moieties.

During the past seven years numerous nitroxides have been synthesized at QUT (Fairfull,

Blinco et al. 2008). These nitroxides possess fluorophore covalently bound within the

structure whereas most of the other nitroxide-fluorophore adducts used by other

researchers have labile covalent linkages that are prone to hydrolysis and resulting

separation of the nitroxide from the fluorophore. This important feature makes the QUT

probes superior to previously synthesized nitroxides because of their enhanced chemical

and thermal stability. All these nitroxide containing fluorophores display substantial

fluorescence suppression. Also, they have the same excitation and emission maxima as the

fluorophore itself. Some of these nitroxides, synthesized at QUT are shown in the Figure 1

together with their excitation and emission wavelengths. These molecules react with

radicals, leading either to reduction of the nitroxides to the hydroxylamines or oxidation to

oxoammonium cation. The measure of the number of radicals trapped by the nitroxides or

other redox reactions that occur is the intensity of the fluorescence emission. These

nitroxides are classified as profluorescent according to the fact that they are initially weakly

fluorescent, but can be transformed into a fluorescent form after a simple chemical

reaction. Taking into account the above, these molecules can serve as powerful optical

74

sensors applicable as detectors of free radicals and dynamic fluorescent indicators of the

overall redox environment in cellular systems (redox active agents).

Figure 1. Structures of some of the profluorescent nitroxides synthesised at QUT together with the

excitation and emission wavelengths of the fluorophores.

A number of profluorescent nitroxide probes were evaluated (Jamriska, Morawska et al.

2004) for their ability to detect and quantify ROS associated with combustion generated

particles. Out of all of the evaluated probes 9,10-bis(phenylethynyl)anthracene-nitroxide

(BPEAnit) was chosen as the most appropriate for use with combustion generated particles

(Miljevic, Fairfull-Smith et al. 2010). The excitation and emission wavelength of the

BPEAnit are long enough to avoid overlapping with the background fluorescence coming

from optically active compounds which may be present in PM.

BPEAnit has been applied in situ to assess the oxidative potential of cigarette smoke

(Miljevic, Fairfull-Smith et al. 2010), diesel particle matter (DPM) (Surawski, Miljevic et al.

2010; Surawski, Miljevic et al. 2011; Surawski, Miljevic et al. 2011) and wood smoke (Zhang,

Flourescein- nitroxide

9,10-bis(phenylethynyl)anthracene- Nitroxide (BPEAnit)

9,10–diphenylanthracene- nitroxide

Phenanthrene-nitroxide

nitroxide

nitroxide

λex

= 294 nm

λem

=355 nm

372 nm

λex

= 495 nm

λem

=515 nm λ

ex= 395 nm

λem

=410 nm

430 nm

λex

= 430 nm

λem

=485 nm

510 nm

75

Jimenez et al. 2007). Samples were collected by bubbling aerosol through an impinger

containing 20 mL of 4 μM BPEAnit solution (using AR grade dimethylsulphoxide as a solvent)

followed by fluorescence measurements with a spectrofluorometer (Ocean Optics). The

amount of BPEAnit reacting with the combustion aerosol was calculated from a standard

curve obtained by plotting known concentrations of the methyl adduct of BPEAnit (BPEAnit-

Me; fluorescent) against the fluorescence intensity at 485 nm. For each setting and

particulate source, two samples were taken. The first one was the result from the exposure

of BPEA solution to the particle-free gas phase, which was done by placing HEPA-filter

between an impinger and an aerosol source. Test sample was collected upon exposure to

both the particle and the gas phase, demonstrating the effect of the particle-related ROS.

Based on the difference in fluorescence signals at 485 nm between the test and HEPA-

filtered control sample, the amount of particle-associated ROS emitted for each test sample

was calculated and normalised to the particle mass to give ROS concentrations (nmol/mg).

3.3. Results and discussion

To investigate the use of the profluorescent nitroxide BPEAnit to detect ROS present in

combustion-generated particles using fluorescence spectroscopy initial experiments were

conducted with cigarette smoke. As one of the most common combustion-generated

aerosols and due to its easy generation, it was taken as a model aerosol. Sampling

mainstream cigarette smoke gave a linear increase of fluorescence intensity with increasing

number of puffs with this pattern being reproducible, although values varied with each

individual cigarette. Sampling much lower concentrations of particles as produced by

sidestream cigarette smoke generated in a test chamber also gave increased fluorescence

intensity with increased sampling time. Since the increase of signal was well above the

detection limit, we have clearly shown the capability of this approach to be successful in

determining the levels and potential toxicological impact of ROS in general studies where

near ambient concentrations of particles are observed. By being able to omit the

derivatisation step, and by undertaking fluorescence measurements immediately after the

sampling, we demonstrated the potential for these probes for the future development of

real time ROS detectors.

76

The BPEAnit was used to further study the potential toxicological impact of particles

produced during biomass combustion by an automatic pellet boiler and a traditional

logwood stove under various combustion conditions (Zhang, Jimenez et al. 2007). The

fluorescence of BPEAnit was measured for particles produced during various combustion

phases, at the beginning of burning (cold start), stable combustion after refilling with the

fuel (warm start) and poor burning conditions. For particles produced by the logwood stove

under cold-start conditions significantly higher amounts of reactive species per unit of

particulate mass were observed compared to emissions produced during a warm start. In

addition, sampling of logwood burning emissions after removing all the semivolatile species

resulted in an 80-100% reduction of the fluorescence signal of BPEAnit probe, indicating

that the majority of reactive species were semivolatile. A significant reduction in PM

oxidative potential after thermal conditioning was also observed by Biswas and co-workers

(Biswas, Verma et al. 2009) who used a dithiothreitol (DTT) assay to measure the oxidative

potential of particulate matter produced by heavy–duty vehicles. As a further support of the

role of organic species in particle induced oxidative stress, we observed strong correlations

(r = 0.85 and 0.99) between the amount of ROS and the mass fraction of organic species in

the PM during cold-start stable combustion and warm-start combustion (Figure 2).

Figure 2. Correlation between the amount of ROS and the amount of organics for stable phase of

cold-start (A), and warm-start (B) logwood burning.

77

The profluorescent nitroxide probe was also applied to study the oxidative potential of

DPM. Emissions from various alternative fuels and diesel engine technologies were

investigated. Fuels investigated included ethanol (Surawski, Miljevic et al. 2009), Fischer-

Tropsch diesel (gas to liquid) (Surawski, Miljevic et al. 2011) and various biodiesel stocks

(soy, canola, tallow) in various blend percentages (Surawski, Miljevic et al. 2011). A similar

picture as with the wood combustion also emerged with a good correlation between the

particle volatile organic content and ROS concentration being observed.

Particles from sidestream cigarette smoke were shown to have 4-9 and 30-80 times less ROS

per unit of mass than particles produced during warm- start and cold-start logwood

combustion, respectively. This finding sheds a new light on logwood smoke particles and

draws attention to the importance of expanding the knowledge on the toxicological

properties of wood smoke particles. Diesel exhaust particles generated under full engine

load were found to have similar ROS concentrations as sidestream cigarette smoke particle

Figure 3. The amount of ROS for stable phase of cold-start (A), and warm-start (B) logwood

burning, side stream tobacco smoke and different operating conditions for ethanol blended diesel

E0 E10

idle

E0 E20

25%

E0 E10 E20 E40

50%

E0 E40

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

5500

6000R

OS

co

nce

ntr

atio

n (

nm

ol m

g-1

)

100%

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

5500

6000

RO

S c

on

ce

ntr

atio

n (

nm

ol m

g-1

)

Burning phase

Cold-

startup

Cold-

stable

Warm(1) Warm(2) Sidestream

cig.smoke

78

These studies also provided an opportunity to look into the correlation between the

physical properties of DPM and oxidative capacity of particles measured as the

concentration of ROS. Toxicological studies, such as (Oberdorster 2001), have pointed to the

particle surface area as a potential metric for assessing the health effects of PM. The

surface area of a particle provides a measure of the ability of toxic compounds (such as

PAHs or ROS) to adsorb or condense upon it. Polycyclic Hydrocarbons (PAHs) are the

principal pollutants from incomplete combustion, and are of special interest due to their

toxicity, carcinogenicity, and ubiquitous presence in the environment (McCrillis, Watts et al.

1992). Therefore, a particle’s surface area can be viewed as a “transport vector” for many

compounds deleterious to human health and requires more detailed analysis.

In addition, it is of urging interest to introduce an effective automated real-time particle-

bound ROS sampling system that will allow routine evaluation of health effects and

monitoring of the pollution. Following this, improvement in the sampling methodology

coupled with the usage of a very sensitive probe such as BPEA nitroxide can provide good

ROS monitor. As previously used technique, liquid impingement, has relatively low and size-

dependent collection efficiency for particles smaller than 500 nm, we are implementing the

usage of particle into liquid sampler (PILS) to overcome this drawback. PILS grows

submicron particles in a condensation growth chamber and subsequently collects them

using a wetted cyclone (Orsini, Rhoads et al. 2008). BPEA nitroxide is used to collect

particles. This approach makes ROS measurements more efficient, less time consuming and

less labor intensive and it is currently being tested.

3.4. Conclusions

An in-house developed methodology for detection of PM–derived ROS by using a

profluorescent nitroxide probe (BPEAnit) has been developed and provided a good basis for

employing the new probe for the assessment of the oxidative potential arising from

particles generated by other combustion sources. Considering that for all three aerosol

sources (i.e. cigarette smoke, diesel exhaust and wood smoke) the same assay was applied,

a direct comparison of the oxidative potential measured for all three sources of particles is

possible. What is even more important is that a good correlation was observed between the

79

semivolatile organic content of combustion particles (both for wood burning and DPM) and

their oxidative capacity as measured through the ROS concentration. This highlights the

importance of semivolatiles in the oxidative potential of the particulate matter. This has far

reaching consequences on how we regulate particle emissions from combustion sources

such as diesel vehicles. For example, the new standards for diesel vehicle engine emissions

(EURO 5/6) are based on measurements of particle number emissions and not particle mass

emissions. The introduction of particle number based standards as opposed to mass based

standards were introduced as the number much better reflects the nanoparticle component

of DPM than simple mass based measurements. To achieve reproducible particle number

measurements, the standards introduce thermal conditioning of the exhaust prior to

sampling. This results in the removal of any semi-volatile organic components from the

exhaust particles. If the semi-volatile organic component is responsible for the oxidative

capacity of particles, and therefore drives their toxicity, the validity of the new diesel vehicle

emission standards has to be brought into question.

3.5. Acknowledgement

Parts of this paper was presented at the 3rd WeBIOPATR workshop, Belgrade 15.-17.

November 2011. This work was supported by the Australian Research Council Centre of

Excellence for Free Radical Chemistry and Biotechnology (CE 0561607), the Australian

Research Council Discovery grant (DP120100126) and Queensland University of Technology.

80

3.6. References

1. Englert, N., Fine particles and human health-a review of epidemiological studies.

Toxicology Letters. Proceedings of EUROTOX 2003. The XLI European Congress of

Toxicology. Science for Safety, 2004. 149(1-3): p. 235-242.

2. Li, N., et al., Induction of Heme Oxygenase-1 Expression in Macrophages by Diesel

Exhaust Particle Chemicals and Quinones via the Antioxidant-Responsive Element. J

Immunol, 2000. 165(6): p. 3393-3401.

3. Li, N., et al., Ultrafine particulate pollutants induce oxidative stress and mitochondrial

damage. Environmental Health Perspectives, 2003. 111(4): p. 455-460.

4. Hetland, R.B., et al., Release of inflammatory cytokines, cell toxicity and apoptosis in

epithelial lung cells after exposure to ambient air particles of different size fractions.

Toxicology in Vitro, 2004. 18(2): p. 203-212.

5. Dellinger, B., et al., Role of free radicals in the toxicity of airborne fine particulate matter.

Chemical Research in Toxicology, 2001. 14(10): p. 1371-1377.

6. Stone, V., H. Johnston, and R.P.F. Schins, Development of in vitro systems for

nanotoxicology: methodological considerations. Critical Reviews in Toxicology, 2009.

39(7): p. 613-626.

7. Cho, A.K., et al., Redox activity of airborne particulate matter at different sites in the Los

Angeles Basin. Environmental Research, 2005. 99(1): p. 40-47.

8. Hasson, A.S. and S.E. Paulson, An investigation of the relationship between gas-phase

and aerosol-borne hydroperoxides in urban air. Journal of Aerosol Science, 2003. 34(4):

p. 459-468.

9. Foucaud, L., et al., Measurement of reactive species production by nanoparticles

prepared in biologically relevant media. Toxicology Letters, 2007. 174(1-3): p. 1-9.

81

10. Ou, B.X. and D.J. Huang, Fluorescent approach to quantitation of reactive oxygen species

in mainstream cigarette smoke. Analytical Chemistry, 2006. 78(9): p. 3097-3103.

11. Ayres, J.G., et al., Evaluating the Toxicity of Airborne Particulate Matter and

Nanoparticles by Measuring Oxidative Stress Potential—A Workshop Report and

Consensus Statement. Inhalation Toxicology, 2008. 20(1): p. 75-99.

12. Fairfull, K.E., et al., A novel profluorescent dinitroxide for imaging polypropilene

degradation. Macromolecules, 2008. 41(5): p. 3.

13. Blinco, J.P., et al., Profluorescent Nitroxides as Sensitive Probes of Oxidative Change and

Free Radical Reactions†. Australian Journal of Chemistry, 2011. 64(4): p. 373-389.

14. Miljevic, B., et al., The application of profluorescent nitroxides to detect reactive oxygen

species derived from combustion-generated particulate matter: Cigarette smoke - A case

study. Atmospheric Environment, 2010. 44(18): p. 2224-2230.

15. Surawski, N.C., et al., Physico-chemical characterisation of particulate emissions from a

compression ignition engine: the influence of biodiesel feedstock. Environmental Science

& Technology, 2011. 45(24): p. 10337-10343.

16. Surawski, N.C., et al., Physicochemical Characterization of Particulate Emissions from a

Compression Ignition Engine Employing Two Injection Technologies and Three Fuels.

Environmental Science & Technology, 2011. 45(13): p. 5498-5505.

17. Surawski, N.C., et al., Particle emissions, volatility and toxicity from an ethanol fumigated

compression ignition engine. Environmental Science & Technology, 2010. 44(1): p. 229-

235.

18. Miljevic, B., et al., Oxidative potential of logwood and pellet burning particles assessed

by a novel profluorescent nitroxide probe. Environmental Science & Technology, 2010.

44(17): p. 6601-6607.

19. Biswas, S., et al., Oxidative potential of semi-volatile and non volatile particulate matter

(PM) from heavy-duty vehicles retrofitted with emission control technologies.

Environmental Science & Technology, 2009. 43(10): p. 3905-3912.

82

20. Surawski, N.C., et al., Particle Emissions, Volatility, and Toxicity from an Ethanol

Fumigated Compression Ignition Engine. Environmental Science & Technology, 2009.

44(1): p. 229-235.

21. Oberdorster, G., Pulmonary effects of inhaled ultrafine particles. International Archives

of Occupational and Environmental Health, 2001. 74(1): p. 1-8.

22. McCrillis, R.C., R.R. Watts, and S.H. Warren, Effects of operating variables on PAH

emissions and mutagenicity of emissions from woodstoves. Journal Name: Journal of the

Air and Waste Management Association; (United States); Journal Volume: 42:5, 1992: p.

Medium: X; Size: Pages: 691-694.

23. Orsini, D.A., et al., A Water Cyclone to Preserve Insoluble Aerosols in Liquid Flow—An

Interface to Flow Cytometry to Detect Airborne Nucleic Acid. Aerosol Science and

Technology, 2008. 42(5): p. 343 - 356.

83

Chapter 4

THE USE OF A NITROXIDE IN DMSO TO CAPTURE FREE

RADICALS IN PARTICULATE POLLUTION

S. Stevanovic,[1,2] B. Miljevic,[1] G.K. Eaglesham,[3] S. E. Bottle,[2] Z. D. Ristovski[1], K. E. Fairfull-

Smith2





3The National Research Centre for Environmental Toxicology (Entox), University of

Queensland, 39 Kessels Road, Queensland 4108, Brisbane, Australia

S. Stevanovic, B. Miljevic, G.K. Eaglesham, S. E. Bottle, Z. D. Ristovski, K. E. Fairfull-Smith, The

Use of a Nitroxide Probe in DMSO to Capture Free Radicals in Particulate Pollution,

European Journal of Organic Chemistry, 012. 2012(30): p. 5908-5912.

84


Title: The Use of a Nitroxide Probe in DMSO to Capture Free Radicals in Particulate Pollution

Authors: S. Stevanovic,[1,2] B. Miljevic,[1] G.K. Eaglesham,[3] S. E. Bottle,[2] Z. D. Ristovski[1], K.

E. Fairfull-Smith2


Made the experimental design, conducted all the experiments, conducted HPLC and LCMS

measurements, performed data analysis and wrote part of the manuscript

Z.Ristovski

Assisted with the manuscript; reviewed the manuscript.

B.Miljevic

Assisted with experimental design and HPLC exeperiments; reviewed the manuscript.


Wrote the manuscript, conducted 1HNMR and 13CNMR experiments; Reviewed manuscript.

G.K. Eaglesham

Assisted with LCMS exeperiments

S.Bottle

Reviewed the manuscript; contributed to the experimental design and data interpretation.

85

The Use of a Nitroxide Probe in DMSO to Capture Free Radicals in Particulate Pollution

S. Stevanovic,[1,2] B. Miljevic,[1] G.K. Eaglesham,[3] S. E. Bottle,[2] Z. D. Ristovski[1], K. E. Fairfull-

Smith2





3The National Research Centre for Environmental Toxicology (Entox), University of

Queensland, 39 Kessels Road, Queensland 4108, Brisbane, Australia

Abstract

A profluorescent nitroxide was used to evaluate the oxidative potential of pollution derived

from a compression ignition engine using biodiesel. The reaction products responsible for

the observed fluorescence increase when a DMSO solution of nitroxide was exposed to

biodiesel exhaust were determined using HPLC/MS. The main fluorescent species was

identified as a methanesulfonamide adduct arising from the reaction of the nitroxide with

DMSO derived sulfoxyl radicals.

Keywords: Atmospheric chemistry / Radicals / Fluorescence / Nitroxides / Environmental

chemistry

86

halla

Due to copyright restrictions, this article cannot be made available here. Please view the published version online at: http://dx.doi.org/10.1002/ejoc.201200903

126

Chapter 5

CHARACTERISATION OF A COMMERCIALLY AVAILABLE

THERMODENUDER AND DIFFUSION DRYER FOR ULTRAFINE

PARTICLE LOSSES

S. Stevanovic1, B. Miljevic1, P. Madl2, S. Clifford1, Z.D. Ristovski1



2 Department of Molecular Biology, Division of Physics and Biophysics, University of Salzburg,

A-5020 Salzburg, Austria

S. Stevanovic, B. Miljevic, P. Madl, S. Clifford, Z.D. Ristovski, Characterisation of a

commercially available thermodenuder and diffusion drier for ultrafine particles losses,

submitted to Aerosol Science and Technology

127


Title: Characterisation of a commercially available thermodenuder and diffusion drier for

ultrafine particles losses

Authors: S. Stevanovic1, B. Miljevic1, P. Madl2, S. Clifford1, Z.D. Ristovski1


Contributed to the experimental design, conducted measurements, performed data analysis

and wrote manuscript.

B.Miljevic

Assisted with the experimental design; Assisted with measurements; reviewed the

manuscript.

P.Madl

Conducted thermo profile experiments.

S.Clifford

Performed statistical analyses of particle losses; reviewed the manuscript.

Z.Ristovski

Contributed to the experimental design, assisted with data interpretation; reviewed the

manuscript.

128

Characterisation of a commercially available thermodenuder and diffusion drier for

ultrafine particles losses

S. Stevanovic1, B. Miljevic1, P. Madl2, S. Clifford1, Z.D. Ristovski1



2 Department of Molecular Biology, Division of Physics and Biophysics, University of Salzburg,

A-5020 Salzburg, Austria

Abstract

Volatility of particles is an important physical property and it directly influences the

chemical composition of aerosols and thus their reactivity and related toxicity.

Thermodenuders (TD) are widely used for the volatility studies, which is primarily giving an

insight into the kinetics of evaporation and condensation within the device. In addition,

characterisation of particle phase component depends on the humidity of the carrier gas

and the presence of semi volatile organic compounds. Diffusion dryers are most commonly

used for the removal of gas phase and volatile organic compounds and water vapour. The

interpretation of data when using thermodenuders and diffusion dryers often excludes the

correction factors that describe particle losses inside these instruments. To address this

deficiency a commercially available TD and diffusion drier were characterised in the

laboratory. For the TD the temperature profiles inside the TD showed optimal results only

within a very narrow flow-window of 1 L/min resulting in inhomogeneous profiles for the

flow rates outside this range. Losses at ambient temperature were very high for particles

smaller than 50nm and were dependent on the particle composition with higher losses

observed for sodium chloride particles. A similar trend was observed for diffusion dryers

where the losses can be up to 50% for particles smaller than 50 nm. From the experimental

results a logistic regression model is fitted to the size dependent loss function. This model

should be used to correct for the losses especially if aerosols smaller than 50nm are studied.

Key words: Thermodenuder, diffusion dryer, particle losses, volatility, regression model

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5.1 Introduction

The importance of organics in particulate toxicity has been widely recognised

(Mauderly and Chow 2008). The organic aerosol (OA) volatility is directly related to its

chemical composition giving us insight into the possible oxidation pathways under

atmospheric conditions (Jonsson et al 2007). The fraction that is believed to contribute the

most to this particle related toxicity is the semi-volatile organic fraction. Depending on the

source and atmospheric conditions this can be significant portion of the aerosols in question

(Robinson, Donahue et al. 2007).

Volatility measurements have been widely performed for over a number of years

((Biswas, Ntziachristos et al. 2007), (Kulmala, Pirjola et al. 2000; 2002; Sakurai, Park et al.

2003; Schönborn, Ladommatos et al. 2009)). Thermodenuders (TDs) are the most commonly

used instruments for near-real time measurement of volatile and non-volatile fraction, both

in the field (Wehner, Philippin et al. 2002) and in the laboratory (An, Pathak et al. 2007;

Jonsson, Hallquist et al. 2007).

TDs are comprised of two sections – one for heating and one for cooling. They are

designed to remove the volatile and semi-volatile fractions by thermal desorption. The

volatile and semi-volatile fractions are heated to achieve complete evaporation and are

trapped by adsorption on activated charcoal in the cooling section.

Proper measurement of volatile fraction must include characterisation of the

temperature profile, particle losses and gas adsorption efficiency in the thermodenuder.

Characterising the temperature profile is important as temperature determines the

residence time inside the TD as well as the efficiency of evaporation. Complete evaporation

presumes uniform temperature in the heating part and an adequate residence time inside

cooling part. Burtscher et al., (Burtscher, Baltensperger et al. 2001) showed that

sedimentation only influences the particle losses in the case of micron particles. In the case

of submicron particles, particle losses inside the TD are mainly caused by thermophoretic

and diffusional processes. The number of data collected with TD’s is growing, but

interpretation of the results is often performed without correcting for transport efficiency

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As a great number of researchers use the commercially available TSI 3065 TD as a

part of their experimental setup (Grosjean, Grosjean et al. 2000; Miljevic, Heringa et al.

2010; Chuepeng, Xu et al. 2011; Xue, Grift et al. 2011) we investigated the performance of

this particular TD. This study highlights the importance of correcting data prior to analysis,

which presumes normalisation of the volatility data for these correction factors.

To determine the relationship between flow rate, particle size and proportion of

particles lost inside each of the TSI 3065 thermodenuder and Topas DDU 570/L diffusion

dryer, a logistic regression model is fitted. The model is a low rank thin plate , a semi-

parametric smoother which is able to flexibly fit non-linear effects (Jamriska, Morawska et

al. 2004). Rather than fitting a polynomial, it is suspected that the losses in a

thermodenuder and diffusion dryer will decrease from a maximum loss for smaller

diameters and eventually transition to a region where the losses are independent of particle

diameter. This behaviour can be modelled with a logistic regression with a low rank thin

plate smoother. For each device, the following model is fit

(1)

where is the predicted loss corresponding to mobility diameter and is the knot for

the thin plate smoother, representing a change point between the two linear models.

Further details of this regression method can be found in the supplementary material.

The other part of this study was an experimental characterisation of aerosol losses

inside diffusion dryers. Diffusion dryers are commonly used to remove some of the gas

phase components such as water vapour or volatile organic compounds (VOCs). In the first

case they are filled with silica gel, while the second case typically features the use of

activated charcoal. They can influence sampling in two ways. First, particle losses will most

likely occur due to diffusion and second, vapour pressure of semi-volatiles might influence

the losses as this can lead to changed particle composition as well as size. As diffusion

dryers are most commonly used to condition aerosols, it is also very important to

investigate the losses that appear inside them.

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5.2 Experimental

5.2.1 a TSI Low-Flow Thermodenuder Model 3065 (TSI-TD)

We used a commercially available low-flow thermodenuder (model 3065, TSI Inc.).

Most of the aerosol-conducting pathway is made of glass. The desorber section of the

instrument uses a 6.35 mm (¼”) in diameter and 120 mm long convoluted stainless steel

tube welded onto a 100 mm long glass “bottleneck” that enlarges to form a shoulder piece

housing the stainless-steel grid pipe required to keep the charcoal-pellets from collapsing

into the aerosol pathway. The steel-glass interface has a slightly thicker diameter than the

steel or the glass section. It was found to be 13 mm in diameter, whereas the glass

extension holding the steel gridpipe at the very end of the desorber section measured

already 20 mm. These variations in diameter are important in order to understand the

temperature profiles outlined further below. Heating of the desorber section is achieved

indirectly by using a heater tape that is wrapped around both the stainless steel pipe and

the glassware attached to it. The thermocouple used to operate the heater control loop of

the instrument is inserted in-between the aerosol-conducting tubing and the heater tape.

The adsorber section of this TD has an outer diameter of about 100 mm and covers a

length of approximately 700 mm. The diameter of the mesh tube through which the aerosol

flows through is ½”. It is capable of holding 6 L of activated charcoal pellets. According to

the specifications, the instrument should be operated at low rates between 0.2 - 2 L/min,

with optimal flow at 0.5 to 1 L/min at a desorptive temperature range covering ambient

temperature all the way up to 400°C.

5.2.2 Topas DDU 570/H diffusion dryer

The Topas 570/H diffusion dryer (70 x 475 mm) consists of an acrylic tube with caps

on both ends and tube connectors (8 mm).The aerosol stream passes through three screen

meshed pipes (10.35 mm inner diameter, 12.51 mm outer diameter) which are surrounded

with activated charcoal. The length of the meshed pipe is 421 mm. Although the length of

the diffusion dryer is shorter than the adsorber section of the TSI TD, due to the flow being

split into 3 screen meshed pipes the residence time within the diffusions drier is similar to

the residence time in the adsorber section of the TSI TD. That is, residence time inside

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diffusion dryer with 3 meshed pipes is the same as if the flow was passed through the pipe

of a same diameter but three times longer. The length of that tube would be approximately

the same as the length of the tube inside TD.

5.2.3 Experimental description:

Losses inside the thermodenuder were measured at three different flow rates (1, 2,

4 L/min) and at two temperatures (room temperature, 150°C and 300°C). The performance

of the thermodenuder was assessed using two types of particles – NaCl and lubricating oil

particles. NaCl was chosen due to its non-volatility under all experimental temperatures and

its ease of generation. The lubricating oil particles where chosen as they mimic the volatile

component of diesel exhaust (He, Ge et al. 2009). Due to their small size (<30nm), the

nucleation mode particles will exhibit large losses.

A nebuliser was used to generate particles from a solution of NaCl (99.0%, Sigma- Aldrich)

and lubricating oil diluted in ultra-pure water and analytical grade ethanol, respectively. The

NaCl particles were dried by passing them through the diffusion dryer, which was filled with

silica gel. Lubricating oil particles were dried by passing the aerosol stream through the

diffusion dryer filled with activated charcoal. The experiments were performed for the

particle size range 30-300 nm. To cover the wide range of particles different NaCl solutions

concentrations were used. The following ten sizes were pre-selected for NaCl to

characterise the losses over the wider size range: 20, 30, 45, 65, 90, 120, 155, 191, 237, 274

nm, and the following four sizes were pre-selected for the lubricating oil particles: 30, 90,

150, 250 nm.

Particle size was pre-selected using Electrostatic Classifier (TSI 3071A). As all the

diameters were measured with scanning mobility particle sizer (SMPS), they represent

mobility diameters. A monodisperse aerosol stream was generated, passed through the

thermodenuder and the size distribution was measured upstream and downstream from

the thermodenuder, a similar setup to the one used by Miljevic et al (2009) but with

impingers replaced by the diffusion dryer. To ensure losses within the tubing were

comparable, the tubes leading to each of the two SMPSs were identical in length.

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A correction factor was introduced to account for the small difference in the

recorded measurements of the two SMPSs. For this purpose the TD was replaced with

conductive tubing and experiment was repeated for 5 sizes (30, 65, 120, 191, 274 nm). A

small, but noticeable difference in particle number concentrations was observed and further

used to calculate the correction factor.

The second set of experiments was performed to assess the losses inside a

commercial diffusion dryer. For this purpose we used commercially available Topas DDU

570/H filled with activated charcoal. The experimental setup and NaCl particle generation

were the same as for the thermodenuder experiments. Maximum recommended flow

through the diffusion dryer is 4 litres per minute, corresponding to a residence time of 1.6 s.

The residence times in our experiments were 6.4 s (1 L/min), 3.2 s (2 L/min) and 1.6 s (4

L/min).

5.2.4 Temperature Profiles

The temperature gradient was recorded by using a 0.5 m long and 1mm thick

thermocouple (TC) attached to a Fluke 80TK TC module and Fluke 75 digital multimeter. The

TC was kept centred in the aerosol conducting pathway by housing it within a small metal

cage. For a given temperature, the TC was gradually inserted into the desorber stage (in

intervals of 10 mm) past the desorber section and further, deep into the proximal section of

the adsorber (altogether approx. 400 mm). Temperature profiles were recorded for flow

rates ranging from 0.3 to 3 L/min for temperatures in the range of 150 to 400°C,

incremented in steps of 50°C. Air flow was generated using a venturi suction system; the

flow rate was measured before and after each temperature scan with a Gilibrator bubble

flow meter. All temperature measurements were performed with an empty adsorber stage;

i.e. the charcoal has been removed to avoid unnecessary contamination.

5.3 Results and Discussion

5.3.1 Temperature Profile: During intensive testing it was found that the thermodenuder

showed optimal results only within a very narrow flow window of 1 L/min. The combined

effect of the glass-metal interface, the various thicknesses of the heater section itself, and

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the loosely packed heater tape explains why the temperature profiles in the lower and

higher flow ranges revealed different profiles (Fig 1). Increasing the flow to 1.5 L/min

resulted in an M-shaped temperature profile; this pattern became even more pronounced

at flow rates of 2 L/min and became extremely distorted at flow rates of 3 L/min. Residence

times at 2 L/min were reduced to 200 ms and 130 ms at 3 L/min, pushing the heated air

bolus far below the threshold temperature value even when the instrument was operated

at maximum desorber temperature.

The temperature profiles reveal that the air cooled rapidly before it reached the desorber

stage. At a flow-rate of 0.3 L/min, with a residence time of about 1.3 s and a set point of

400°C the maximum temperature in the heating section was over 450°C. By the time the air

had reached the desorber section it was cooled down to below 250°C. By increasing the

flow to at least 1.5 L/min (with a residence time of 760 ms), the 400°C hot bolus enters the

adsorber stage with a temperature of 250°C and a much more uneven temperature profile

(see Figure 1).

Figure 1. Temperature profile of the TSI-TD at 0.5 and 1.5 L/min. At a flow-rate of 0.5 L/min

(left) the heated bolus of air it is not pushed fast enough to the adsorber stage and as a result

cools off still within the desorber tube, while a flow rate exceeding 1 L/min (right) results in very

distorted temperature profiles.

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5.3.2 Losses inside thermodenuder

Particle losses inside the thermodenuder are result from the combination of three

processes: sedimentation, diffusion and thermophoresis. As mentioned, sedimentation will

not influence the particle number losses of small particles used in the experiments.

Figure 2. Open circles ( ) indicate measured particle number losses for NaCl particles at room

temperature and at three different flow rates (1 L/min, 2 L/min, 4 L/min). The full line is the

predicted losses in TSI 3065 based on the logistic regression model, with the dashed line

representing the 95% confidence intervals.

Figure 2 presents number losses observed in the thermodenuder at room temperature. The

effect of flow rate was found to be negligible in exploratory analysis and it was removed

from the regression model. At room temperature measured losses are assigned to diffusion

effects that increase as particle size decreases. As expected, the observed losses for NaCl

particles are the greatest in the size range below 50nm. The change point between the two

linear models occurred at 66nm. The particle losses are largest for the small particle sizes

and the predicted values from the model are in a good agreement with the experimental

data (R2 = 0.874).

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Particle number losses for NaCl and lubricating oil at 300ºC and at three different

flowrates are shown in Figure 3. As mentioned before, diffusive losses change for different

particle sizes, while thermophoretic losses are not size dependent for particles in the

investigated size-range (Burtscher, Baltensperger et al. 2001). Thermophoresis will act to

force particles towards the tube centre in the desorbing part and then towards the tube

walls as the particle stream enters the adsorbing section. In the case of perfect laminar flow,

the overall effect would be zero.

Figure 3. Particle number losses as a function of size for NaCl and lubricating oil particles at 300C

and three selected flow rates (1 L/min, 2 L/min, 4 L/min)

The number losses curve for NaCl (Fig 4.) shows that at elevated temperature

(300°C) particle losses are similar as those at room temperature.

In the case of lubricating oil, however, particle losses increase with temperature.

This trend is more obvious at lower flow rates, when particles experience longer residence

time inside the TD. The evaporation of semi-volatile components during these long

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residence times leads to a reduced particle size, resulting in larger diffusional losses. The

combination of evaporation, diffusion and thermophoretic effects leads to a removal of 99%

of particles smaller than 50 nm.

To illustrate the evaporation process that is occurring when lubricating oil particles

are exposed to elevated temperature, the sizes of pre-selected particles before and after

the thermodenuder were measured (Fig. 4). Lubricating oil particles evaporate and their

diameter decreases significantly. This effect is the most pronounced for the long residence

times at the lowest flow rate (1 L/min). This reduction in size leads to increased diffusional

losses and explains increased particle losses below 50 nm observed in Fig.2. No change in

particle diameter was observed for NaCl particles as they are non volatile.

It is also of note that there are no changes in the particle size for lubricating oil particles at

room temperature. Although the air passes through the adsorber section, resulting in

absorption of the vapour phase of semivolatile components, the residence time is not

sufficiently long for any evaporation from the particle phase to occur.

Figure 4. Measured size of pre-selected NaCl and lubricating oil particles before and after

thermodenuder at room temperature and at 300C .The flow rates of aerosol stream were 1

L/min, 2 L/min and 4 L/min.

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5.3.3 Losses inside diffusion dryer

In this section, losses of NaCl particles inside diffusion dryers that were filled with

activated charcoal at room temperature were investigated. As previously mentioned, the

observed losses may be assigned to a process of diffusion. Figure 5 illustrates particle

number losses that were observed at three different flow rates.

Fig. 5 Open circles (○) indicate measured NaCl particle losses in Topas DDU 570/L diffusion dryer

for 1, 2 and 4 L/min, at room temperature. The full line is the predicted losses based on the logistic

regression model, with the dashed line representing the 95% confidence intervals.

As with TD particle losses for NaCl at room temperature, the biggest losses (15-50%)

are for small particles with diameters smaller than 50 nm. The change point occurs at 93nm.

The main losses in the thermodenuder for small particles are in the adsorber section, which

is similar in design to the dryer, i.e. mesh surrounded by charcoal. Number losses for

particles bigger than 65 nm are considerably smaller and they are negligible for particles

bigger than 0.1 µm. Model fit for the thin plate smoother shows good agreement with the

data (R2 = 0.712).

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5.4 Conclusion

As indicated by the temperature profiles (Figure 1), the design of the TSI 3065

thermodenuder’s heater stage makes it very difficult to keep the desorber temperature

above the required threshold temperature of 250°C. As discussed by Wehner et al. (2002)

the small dimensions of the desorber stage, which result in short residence times, are the

main reason for the incomplete desorptive properties. As the temperature in the

desorption stage decreases, only partial removal of the volatile fraction is achieved. An

increase in flow (>1 L/min) slightly compensated for this steep temperature drop, but

resulted in an inhomogeneous temperature profile within the heater stage. Such M-shaped

temperature fluctuations within the desorber stage are a result of the various thermal

properties of steel and glass – especially at the interface. These fluctuations are undesirable

as they result in the formation of particles after the initial temperature peak and there is

insufficient time for thermal dissolution when exposed to the second thermal peak

(Burtscher, Baltensperger et al. 2001).

The investigated thermodenuder has relatively high losses for small particles. The results

presented indicate that these losses are higher for smaller particles and higher

temperatures, which is consistent with a common pattern that is reported in

thermodenuder characterisations. In order to correct for the losses we have fitted the loss

function according to Eq. 1. The loss function for this type of thermodenuder for all flow

rates can be expressed as:

where µ is the loss function and d is the mobility diameter of the particle expressed in

nanometres. The fitted function together with the 95% confidence interval is shown on

Figure 2.

Diffusion dryers are also commonly used to precondition the inlet air of instruments, either

to remove the moisture (dry the air and particles) or to remove the gas phase semivolatile

organic species (Venkatachari and Hopke 2008). If significant portions of the aerosol

140

particles are in the size range bellow 50 nm a correction for the losses within the diffusion

dryer is necessary as the losses can be as large as 50% at this size. To enable the correction

we have used the same mathematical model as for the TD (Eq.1) and applied it for the

measurements conducted for the diffusion drier. The fitted curve together with the 95%

confidence interval is shown on Figure 5. The loss function for this type of diffusion drier for

all flow rates can be expressed as:

In the case of lubricating oil (a surrogate for semivolatile aerosols observed in diesel

exhaust) a significant reduction in the vapour pressure, due to absorption in the charcoal

filled diffusion dryer, will not lead to the change in the composition of particles and

evaporation of lower volatility compounds over residence times of several seconds

exhibited in the dryers.

5.5 References:

An, W. J., R. K. Pathak, et al. (2007). "Aerosol volatility measurement using an improved

thermodenuder: Application to secondary organic aerosol." Journal of Aerosol

Science 38(3): 305-314.

Biswas, S., L. Ntziachristos, et al. (2007). "Particle volatility in the vicinity of a freeway with

heavy-duty diesel traffic." Atmospheric Environment 41(16): 3479-3493.

Burtscher, H., U. Baltensperger, et al. (2001). "Separation of volatile and non-volatile aerosol

fractions by thermodesorption: instrumental development and applications." Journal

of Aerosol Science 32(4): 427-442.

Gramacy, R. B. (2007). "tgp: An R package for Bayesian nonstationary, semiparametric

nonlinear regression and design by treed Gaussian process models." Journal of

Statistical Software 19(9): 1-46.

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Gramacy, R. B. and H. K. H. Lee (2008). "Bayesian treed Gaussian process models with an

application to computer modeling." Journal of the American Statistical Association

103(483): 1119-1130.

Johnson, G. R., Z. Ristovski, et al. (2004). "Method for measuring the hygroscopic behaviour

of lower volatility fractions in an internally mixed aerosol." Journal of Aerosol

Science 35(4): 443-455.

Johnson, G. R., Z. D. Ristovski, et al. (2005). "Hygroscopic behavior of partially volatilized

coastal marine aerosols using the volatilization and humidification tandem

differential mobility analyzer technique." J. Geophys. Res. 110(D20): D20203.

Jonsson, Å. M., M. Hallquist, et al. (2007). "Volatility of secondary organic aerosols from the

ozone initiated oxidation of α-pinene and limonene." Journal of Aerosol Science

38(8): 843-852.

Kondo, Y., L. Sahu, et al. (2009). "Stabilization of the Mass Absorption Cross Section of Black

Carbon for Filter-Based Absorption Photometry by the use of a Heated Inlet."

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Kulmala, M., L. Pirjola, et al. (2000). "Stable sulphate clusters as a source of new

atmospheric particles." Nature 404(6773): 66-69.

Kuwata, M., Y. Kondo, et al. (2007). "Dependence of CCN activity of less volatile particles on

the amount of coating observed in Tokyo." J. Geophys. Res. 112(D11): D11207.

Mauderly, J. L. and J. C. Chow (2008). "Health Effects of Organic Aerosols." Inhalation

Toxicology 20(3): 257-288.

Meyer, N. K. and Z. D. Ristovski (2007). "Ternary Nucleation as a Mechanism for the

Production of Diesel Nanoparticles: Experimental Analysis of the Volatile and

Hygroscopic Properties of Diesel Exhaust Using the Volatilization and Humidification

Tandem Differential Mobility Analyzer." Environmental Science & Technology 41(21):

7309-7314.

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Nord, K. E. and D. Haupt (2005). "Reducing the Emission of Particles from a Diesel Engine by

Adding an Oxygenate to the Fuel." Environmental Science & Technology 39(16):

6260-6265.

Robinson, A. L., N. M. Donahue, et al. (2007). "Rethinking organic aerosols: semivolatile

emissions and photochemical aging.(REPORTS)." SCIENCE 315(5816): 1259(1254).

Ruppert, D., M. P. Wand, et al. (2003). Semiparametric Regression, Cambridge University

Press.

Sakurai, H., K. Park, et al. (2003). "Size-Dependent Mixing Characteristics of Volatile and

Nonvolatile Components in Diesel Exhaust Aerosols." Environmental Science and

Technology 37(24): 5487-5495.

Sakurai, H., H. J. Tobias, et al. (2003). "On-line measurements of diesel nanoparticle

composition and volatility." Atmospheric Environment 37(9–10): 1199-1210.

Venkatachari, P. and P. K. Hopke (2008). "Development and Laboratory Testing of an

Automated Monitor for the Measurement of Atmospheric Particle-Bound Reactive

Oxygen Species (ROS)." Aerosol Science and Technology 42(8): 629 - 635.

Wehner, B., S. Philippin, et al. (2002). "Design and calibration of a thermodenuder with an

improved heating unit to measure the size-dependent volatile fraction of aerosol

particles." Journal of Aerosol Science 33(7): 1087-1093.

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5.6 Supplementary material

(Ruppert, Wand et al. 2003) define a univariate low rank thin plate spline as the sum

of a polynomial fixed effect and polynomial random effects. The partial effect of a low rank

thin plate spline with J random effects of order p as

where κ are the knots (control points) of the spline and are usually placed at the J + 2

quantiles of x. The order of the random effects, p, is chosen to be low (typically 1 to 3), as is

the order of the fixed effect (typically chosen to be linear).The low rank thin plate spline is

an example of semi-parametric regression and provides a balance between flexible

modelling and interpretable parameters. The parameters to be estimated in the regression

model are and γ parameters.

The regression model in this paper uses the logistic link function,

, as the response

variable is the proportion of particles lost and can only take values between 0 and 1. To

determine the location of the single knot in the regression model as a change point, a treed

Gaussian process with a piecewise linear mean function is fit to the data (Gramacy 2007;

Gramacy and Lee 2008). Because the regression uses the logistic link, the treed GP is

inappropriate for the full modelling as the 95 CIs should be heavily asymmetric at values

near 0 and 1. Fitting of this logistic GLM is performed in R with the glm function. Confidence

intervals for the fitted low rank thin plate spline are obtained from glm and are

appropriately asymmetric because the logistic function is not a linear transformation.

Losses were measured at the following sizes (in nanometres): 20, 30, 45, 65, 90, 120, 155,

191, 237 and 274. The change points were 66 for the thermodenuder and 93 for the

diffusion dryer.

144

Flow rate had been included in the regression model but was found to have a negligible

effect in each case (the coefficient for a linear term was zero with p values of 0.8792 for the

thermodenuder and 0.9686 for the diffusion dryer) so flow rate was ignored in the

regression modelling.

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Chapter 6

A PHYSICO-CHEMICAL CHARACTERISATION OF

PARTICULATE EMISSIONS FROM A COMPRESSION IGNITION

ENGINE: THE INFLUENCE OF BIODIESEL FEEDSTOCK

N.C. Surawski1,2, B. Miljevic1, G.A. Ayoko3, S. Elbagir3, S. Stevanovic1,4, K.E. Fairfull-Smith4,

S.E. Bottle4, Z.D. Ristovski1



2 School of Engineering Systems, Queensland University of Technology, 2 George St, Brisbane

QLD 4001, Australia

3Discipline of Chemistry, Queensland University of Technology, 2 George St, Brisbane QLD

4001, Australia

4ARC Centre of Excellence for Free Radical Chemistry and Biotechnology, Queensland University of

Technology, 2 George St, 4001 Brisbane, Australia

Surawski, N. C.; Miljevic, B.; Ayoko, G. A.; Elbagir, S.; Stevanovic, S.; Fairfull-Smith, K. E.;

Bottle, S. E.; Ristovski, Z. D., A physico-chemical characterisation of particulate emissions

from a compression ignition engine: the influence of biodiesel feedstock, Environmental

Science & Technology 2011. 45(24): p. 10337-10343.

146


Title: A physico-chemical characterisation of particulate emissions from a compression

ignition engine: the influence of biodiesel feedstock

Authors: N.C. Surawski1,2, B. Miljevic1, G.A. Ayoko3, S. Elbagir3, S. Stevanovic1,4, K.E. Fairfull-

Smith4, S.E. Bottle4, Z.D. Ristovski1

N. C. Surawski

Contributed to the experimental design, conducted particle number size distribution and

mass measurements, performed data analysis, wrote most of the manuscript

B. Miljevic

Contributed to the experimental design, conducted measurements, data analysis, and

manuscript writing related to the BPEAnit assay.

G. A. Ayoko

Involved with the PAH measurement experimental design, data analysis and manuscript

writing.

S. Elbagir

Involved with the PAH extraction and quantification, and also data analysis.

S. Stevanovic (candidate)

Assisted with ROS measurements; performed data analysis; reviewed the manuscript


Reviewed manuscript; assisted with the interpretation of the ROS measurements.

147

S. E. Bottle

Reviewed the manuscript; assisted with the interpretation of the ROS measurements.

Z. D. Ristovski

Came up with the original idea; contributed to the experimental design, assisted with data

interpretation; reviewed the manuscript

148

A physico-chemical characterisation of particulate emissions from a compression ignition

engine: the influence of biodiesel feedstock

N.C. Surawski1,2, B. Miljevic1, G.A. Ayoko3, S. Elbagir3, S. Stevanovic1,4, K.E. Fairfull-Smith4,

S.E. Bottle4, Z.D. Ristovski1

Abstract

This study undertook a physico-chemical characterisation of particle emissions from a single

compression ignition engine operated at one test mode with 3 biodiesel fuels made from 3

different feedstocks (i.e. soy, tallow and canola) at 4 different blend percentages (20%, 40%,

60% and 80%) to gain insights into their particle-related health effects. Particle physical

properties were inferred by measuring particle number size distributions both with and

without heating within a thermodenuder (TD) and also by measuring particulate matter

(PM) emission factors with an aerodynamic diameter less than 10 μm (PM10). The chemical

properties of particulates were investigated by measuring particle and vapour phase

Polycyclic Aromatic Hydrocarbons (PAHs) and also Reactive Oxygen Species (ROS)

concentrations. The particle number size distributions showed strong dependency on

feedstock and blend percentage with some fuel types showing increased particle number

emissions, whilst others showed particle number reductions. In addition, the median

particle diameter decreased as the blend percentage was increased. Particle and vapour

phase PAHs were generally reduced with biodiesel, with the results being relatively

independent of the blend percentage. The ROS concentrations increased monotonically

with biodiesel blend percentage, but did not exhibit strong feedstock variability.

Furthermore, the ROS concentrations correlated quite well with the organic volume

percentage of particles – a quantity which increased with increasing blend percentage. At

higher blend percentages, the particle surface area was significantly reduced, but the

particles were internally mixed with a greater organic volume percentage (containing ROS)

which has implications for using surface area as a regulatory metric for diesel particulate

matter (DPM) emissions.

149

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169

Chapter 7

THE INFLUENCE OF OXYGENATED ORGANIC AEROSOLS (OOA)

ON THE OXIDATIVE POTENTIAL OF DIESEL AND BIODIESEL

PARTICULATE MATTER

S. Stevanovic1,2, B. Miljevic1, N.C. Surawski, K.E. Fairfull-Smithb, S.E. Bottleb, R.

Brownd, Z.D. Ristovskia,d*





S. Stevanovic, Z.D. Ristovski, B. Miljevic, K. E. Fairfull-Smith, R.Brown, S. E. Bottle, The

influence of oxygenated organic aerosols (OOA) on the oxidative potential of diesel and

biodiesel particulate matter, Environ Sci Technol. 2013; 47(14): p. 7655-62

170


Title: The influence of oxygenated organic aerosols (OOA) on the oxidative potential of

diesel and biodiesel particulate matter

Authors: S. Stevanovic, B. Miljevic, K. E. Fairfull-Smith, S. E. Bottle, R. Brown, Z.D. Ristovski


Contributed to the experimental design, conducted measurements, complete data analysis;

wrote the manuscript.

B.Miljevic

Conducted AMS measurements and AMS data analysis; reviewed the manuscript.


Assisted with data interpretation; reviewed the manuscript.

S.Bottle

Assisted with data interpretation; reviewed the manuscript.

R.Brown

Reviewed the manuscript.

Z.Ristovski

Contributed to the design of the study; assisted with the manuscript; reviewed the

manuscript.

171

The influence of oxygenated organic aerosols (OOA) on the oxidative potential of diesel

and biodiesel particulate matter

S. Stevanovic1,2, Z.D. Ristovski1, B. Miljevic1, K. E. Fairfull-Smith2, S. E. Bottle2





Abstract

Generally, the magnitude of pollutant emissions from diesel engines running on biodiesel

fuel is ultimately coupled to the structure of respective molecules that constitutes the fuel.

Previous studies demonstrated the relationship between organic fraction of PM and its

oxidative potential. Herein, emissions from a diesel engine running on different alternative

fuels were analysed into a more detail to explore the role different organic fractions play in

the measured oxidative potential. In this work, a more detailed chemical analysis of

biodiesel PM was undertaken using a compact Time of Flight Aerosol Mass Spectrometer (c-

ToF AMS). This enabled a better identification of the different organic fractions that

contribute to the overall measured oxidative potentials. Therefore the oxidative potential of

the PM, measured through the ROS content, although proportional to the total organic

content in certain cases shows a much higher correlation with the oxygenated organic

fraction. This highlights the importance of knowing the surface chemistry of particles for

assessing their health impacts. It also sheds a light onto new aspects of particulate

emissions that should be taken into account when establishing relevant metrics for health

implications of emissions from various future fuels.

172

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189

Chapter 8

ENGINE PERFORMANCE CHARACTERISTICS FOR BIODIESELS

OF DIFFERENT DEGREES OF SATURATION AND CARBON

CHAIN LENGTHS

P. Pxam3, T.A.Bodisco2, S. Stevanovic2, M.D.Rahman1, H.Wang1, S.E, R. Brown2,

Z.D. Ristovsk1*, A.R.Masri3



2School of Engineering Systems, Queensland University of Technology, 2 George St, Brisbane

QLD 4001, Australia

3The University of Sydney

P.X. Pham, T.A. Bodisco, S. Stevanovic, M.D. Rahman, W. Hao, Z.D. Ristovski, R.J. Brown ,

A.R. Masri, Engine Performance Characteristics for Biodiesels of Different Degrees of

Saturation and Carbon Chain Lengths , SAE Int. J. Fuels Lubr., 2013, 6 (1)

190


Title: Engine Performance Characteristics for Biodiesels of Different Degrees of Saturation and

Carbon Chain Lengths

Authors: P.X. Pham, T.A. Bodisco, S. Stevanovic, M.D. Rahman, W. Hao, Z.D. Ristovski, R.J.

Brown , A.R. Masri,

P.X.Pham

Contributed to the experimental design, conducted measurements, data analysis; wrote the

manuscript.

T.A.Bodisco

Conducted to the experimental design and data analysis; reviewed the manuscript.


Contributed to the experimental design, conducted measurements, data analysis, and

manuscript writing related to theROS measurements; reviewed the paper

M.D.Rahman

Contributed to the experimental design, conducted measurements;

H.Wang

Contributed to the experimental design

R.Brown

Reviewed the manuscript

191

A.Masri

Contributed to the design of the study; assisted with the manuscript; reviewed the manuscript

Z.Ristovski

Contributed to the design of the study; assisted with the manuscript; reviewed the manuscript

192

Engine Performance Characteristics for Biodiesels of Different Degrees of Saturation and

Carbon Chain Lengths

P.X. Pham, T.A. Bodisco, S. Stevanovic, M.D. Rahman, W. Hao, Z.D. Ristovski, R.J. Brown , A.R.

Masri

1International Laboratory for Air Quality and Health, Queensland University of Technology, GPO

Box 2434, 4001, Brisbane, Australia

2School of Engineering Systems, Queensland University of Technology, 2 George St, Brisbane

QLD 4001, Australia

3The University of Sydney

ABSTRACT

This experimental study examines the effect on performance and emission outputs of a

compression ignition engine operating on biodiesels of varying carbon chain length and the

degree of unsaturation. A well-instrumented, heavy-duty, multi-cylinder, common-rail, turbo-

charged diesel engine was used to ensure that the results contribute in a realistic way to the

ongoing debate about the impact of biofuels. Comparative measurements are reported for

engine performance as well as the emissions of NOx, particle number and size distribution, and

the concentration of the reactive oxygen species (which provide a measure of the toxicity of

emitted particles).

It is shown that the biodiesels used in this study produce lower mean effective pressure,

somewhat proportionally with their lower calorific values; however, the molecular structure

has been shown to have little impact on the performance of the engine. The peak in-cylinder

pressure is lower for the biodiesels that produce a smaller number of emitted particles,

compared to fossil diesel, but the concentration of the reactive oxygen species is significantly

higher because of oxygen in the fuels.

The differences in the physicochemical properties amongst the biofuels and the fossil

diesel significantly affect the engine combustion and emission characteristics. Saturated short

193

chain length fatty acid methyl esters are found to enhance combustion efficiency, reduce NOx

and particle number concentration, but results in high levels of fuel consumption.

Key words: Biodiesel, fatty acid methyl ester, saturation degree, unsaturation degree, chain

length, iodine value, saponification number, NOx, particle mass concentration, particle size

distribution, reactive oxygen species.

halla

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242

Chapter 9

CONCLUSIONS

Particulate pollution has been widely recognised as an important risk to human

health with $3.7 billion spent on respiratory diseases in Australia alone. Exposure to fine PM

leads to increased respiratory and cardiovascular diseases (Englert, 2004). Recently, the

International Agency for Research on cancer (IARC), which is a part of World Health

Organisation (WHO) classified diesel exhaust as carcinogenic to humans (Group 1) on the

12th June 2012, based on sufficient evidence that exposure increases risk for lung cancer.

One of the important aspects of environmental sciences in the last decade was to

identify the physical and chemical properties of PM responsible for the observed effects.

Oxidative stress, caused by generation of free radicals and other ROS at the sites of

deposition, has been proposed as a leading contender to explain adverse health outcomes

associated with exposure to PM.

An in-house developed methodology for PM-related ROS detection by using a

profluorescent nitroxide probe (BPEAnit) has been developed previously. It provided a good

basis for employing this probe for the assessment of the oxidative potential arising from

combustion generated aerosols. This probe has been tested for different combustion

sources and proved to be sufficiently sensitive and robust enough to provide a rapid

estimate of the oxidative potential of PM.

This research program made a significant contribution to our understanding of the

chemistry behind the fluorescence increase of free radical quencher BPEAnit when exposed

to PM. The basis of this research project was to gain more insight into the reaction

mechanism of BPEAnit fluorescence increase when exposed to diesel and biodiesel PM and

to explore the contribution of different organic fractions to the overall redox content.

Following the growing need for adoption of alternative fuels, this project aimed at

getting more information on the OP of biodiesel PM. Within this scope, the physical and

243

chemical characteristics of biodiesel PM were analysed which lead to identification of

reactive organic fractions. It was previously established that the measured ROS content is

dependent on the presence of organic compounds. Semi-volatile organic fraction has been

recognised as a most potent one in regards to negative health effects.

Generally, the magnitude of pollutant emissions from diesel engines running on

biodiesel is ultimately coupled to the structure of respective molecules that constitute the

fuel. The presence of oxygen inside the biodiesel molecules leads to significant levels of

oxygenated toxic species.

During the course of this research project, it was demonstrated that the oxidative

potential, as measured through the levels of ROS concentration, although proportional to

the total volatile organic volume percentage, shows a much stronger correlation to the

oxygenated organic fraction. In addition, the carbon chain length and the degree of

unsaturation inside the fuel molecules strongly influence the biofuel combustion chemistry.

9.1 Principal significance of the findings

The first manuscript in this thesis provided an overview of the measurements of ROS

concentrations from different combustion PMs by using BPEAnit probe. The new technique

employing a novel, profluorescent nitroxide was used for the assessment of oxidative

potential arising from particles generated by three combustion sources.

This paper presented a summary of previous work and provided directions for future

research in this field. It was specifically indicated that the relationship between organic

content of PM and related OP has to be explored into more detail and thus provide a better

platform for understanding of the processes behind their toxicity. The documented role of

semi-volatile compounds in the OP of PM has far reaching consequences on the regulations

of particulate emissions from combustion sources.

For instance, the introduction of particle number standards as opposed to mass

based regulations, were introduced for diesel vehicle engine emissions (EURO5/6). The new

standards better reflect the nanoparticle component of DPM when compared to mass based

244

measurements. However, to achieve reproducible particle number measurements, thermal

conditioning of the exhaust is necessary. This causes the removal of semi-volatile

components. This brings up the question on the validity of the new diesel vehicle emission

standards if the fact that semi-volatile organic component drives the toxicity of PM is taken

into account. Finally, the urge for more research in this field is evident and the following

publications in this thesis are aimed to shed a new light onto this topic.

The second manuscript provided a better insight into the underlying chemistry

leading to fluorescence generated from BPEAnit when exposed to PM. Previously, the

overall increase of fluorescence was measured and then normalised to the concentration of

known fluorescent adduct of BPEAnit, BPEA-Me. However, several compounds, adducts of

profluorescent nitroxide are contributing to the measured fluorescence and not all of these

products have the same quantum yield.

In this manuscript, a methansulfonamide, DMSO derived adduct, was identified as

the main fluorescent species resulting from the reaction of aerosol derived biodiesel

exhaust from the solution of BPEAnit in DMSO. This result improves the interpretation of

reported results and prevents the possible underestimation of ROS concentrations on

particles.

A complete understanding of the mechanisms by which biodiesel derived PM

interacts with DMSO still remain unclear, but it is interesting to note that the same product

could also be generated upon exposure of BPEAnit to higher concentrations of hydrogen

peroxide (HP) and peroxyl radicals and upon sonication of nitroxide in DMSO. HP and

peroxyl radicals are common constituents of diesel exhaust. Also, within the scope of this

study, some other model compounds were chosen and tested to present selectivity and

positive response of BPEAnit to the compounds and species that are likely to be found in

diesel exhaust and other combustion generated PM.

Also, an important finding has been highlighted. The sonication process, which is the

most commonly, used technique for the removal of particles from filters, triggers the

generation of free radicals from solvents and leads to overestimation of measured OP. It can

also change the paths of chemical transformations of species in the liquid phase.

245

This is also the first example of the use of profluorescent nitroxide to detect free

radicals through DMSO sonication. Results from this study improve the ability to quantify

free radicals and related ROS derived from diesel/biodiesel and are an important step

towards the ultimate goal of directly detecting free radicals and related ROS in PM. This is

an important step towards future improvements in air quality assessment.

The third manuscript is aimed to improve the methodology of aerosol sampling and

get information on the particle losses and efficiency of of a commercially available

thermodenuder and a diffusional dryer, two most commonly used instruments.

Thermodenuders are widely used for the measurement of volatile organic fraction of PM

which is already mentioned and recognised as a very important component that can

influence PM composition and kinetics of evaporation. The investigated thermodenuder,

TSI 3065, has relatively high losses for small particles. The results presented in this paper

indicate that the losses are higher for smaller particles and higher temperatures. Fitted loss

function was given:

where µ is the loss function and d is the mobility diameter of the particle expressed in

nanometres. The fitted function holds the 95% confidence interval and can be applied to all

the flow rates.

Also, as one of the main operative parameter, thermal profiles of the desorber stage

were analysed and some limitations were reported. The design of the TSI 3065

thermodenuder’s heater stage makes it very difficult to keep the desorber temperature

above the required threshold temperature of 250°C. As the temperature in the desorption

stage decreases, only partial removal of the volatile fraction is achieved. An increase in flow

(>1 L/min) slightly compensated for this steep temperature drop, but resulted in an

inhomogeneous temperature profile within the heater stage. These fluctuations are

undesirable as they result in the formation of particles after the initial temperature peak

and there is insufficient time for thermal dissolution when exposed to the second thermal

peak. The results presented here highlighted the importance of taking into account all the

factors that may lead to bias in performed measurements and subsequent data analysis.

246

Diffusion driers are also widely used to precondition the inlet air of instruments,

either to remove the moisture (dry the air and particles) or to remove the gas phase

semivolatile organic species. If significant portions of the aerosol particles are in the size

range bellow 50 nm a correction for the losses within the diffusion dryer is necessary as the

losses can be as large as 50% at this size. To enable the correction we have used the same

mathematical model as for the TD and applied it for the measurements conducted for the

diffusion drier. The loss function for this type of diffusion drier for all flow rates can be

expressed as:

The study has also shown that in the case of lubricating oil (a surrogate for semivolatile

aerosols observed in diesel exhaust) a significant reduction in the vapour pressure, due to

absorption in the charcoal filled diffusion dryer, will not lead to the change in the

composition of particles and evaporation of lower volatility compounds over residence

times of several seconds exhibited in the dryers.

The fourth manuscript investigated DPM physico-chemical properties with a direct

injection engine using biodiesel fuels made from 3 different feedstocks each tested with at

least 4 blend percentages. All biodiesel fuel types and blend percentages were very

effective at reducing DPM mass, although the DPM number results exhibited more

complicated trends. Whilst larger soy and tallow biodiesel blend percentages reduced

particle number emissions, other fuel types (especially canola blends) increased the number

of particles emitted. For all the biodiesel fuel types investigated, as the biodiesel blend

percentage was increased, the particles were internally mixed with more ROS on the

particle surface. The semi-volatile organic component of particles was significant and it was

shown that it correlated well with ROS emission factors. However, it was also shown that

the values for oxidative potential didn`t exhibit stock dependency and considerable scatter

in the relationship with volatile component was observed in certain cases. As a result, the

factors leading to increased ROS emissions with oxygenated fuels needs to be explored in

further detail to achieve reductions in this pollutant. This study was a motivation to further

explore this relationship and gain more knowledge on the potent fraction of PM.

247

The fifth study investigated the influence of oxygenated organic aerosols (OOA) on

the oxidative potential of diesel and biodiesel PM. Previous studies have demonstrated that

there is a relationship between the organic fraction and the OP of PM. All of the previous

studies have shown that the semi-volatile component of PM is the most important factor

influencing the OP of these particles. Although a clear link exists between the OP and the

organic fraction of PM, in the case of biodiesel PM no correlation was observed when ROS

concentration was plotted against organic volume percentage. This indicates that the

relationship between these two parameters is complex and more detailed investigation

needs to be undertaken before it will be possible to rationalise the observed results. In this

work a more detailed chemical analysis of PM was conducted using C-ToF AMS which

enabled a better identification of the different organic fractions that contribute to the

overall measured oxidative potentials. The challenging task was to identify the specific PM

fraction that represents the most important causal pollutant component. In order to gain

further insight into the chemical composition of organic aerosol (OA), a tracer method m/z

was used. The types of organic aerosols investigated were hydrocarbon-like OA (HOA) and

oxygenated OA (OOA) species. Two markers were used, f44 and f57, which reflected the

contribution of the particular organic fragment at each molecular ion ( m/z = 44 or 57) to

the total organic mass. From these results it can be concluded that in general the oxidative

potential of the PM, as measured through the levels of ROS concentration, although

proportional with the total volatile organic volume percentage, shows a much stronger

correlation to the oxygenated organic fraction. It also shows the importance of the surface

chemistry for assessing the health impacts and calls for the attention when the appropriate

metrics for air quality are being implemented.

The sixth study was performed to show the differences in the physicochemical

properties amongst the biofuels and the fossil diesel which subsequently significantly affect

the engine combustion and emission characteristics. Generally, the magnitude of pollutant

emissions from diesel engines running on biodiesel fuel is ultimately coupled to the

structure of respective molecules that constitutes the fuel. The presence of oxygen inside

the biodiesel molecules leads to significant levels of oxygenated toxic species. In addition,

the carbon chain length and the degree of unsaturation influence the biofuel combustion

chemistry and these are all dependent on the feedstock. To gain an insight into the

248

relationship between the molecular structure of the esters present in different biodiesel

stocks and their respective oxidative potentials, measurements were conducted on a

modern common rail diesel engine. Tests were designed to present emissions differences

due to changes in fuel, speed and load settings, which included usage of three blends for

every biodiesel feedstock (B20, B50, B100). To establish the oxidative potential of diesel

particles the concentration of ROS was measured using the profluorescent nitroxide probes

developed at QUT. The results indicate that there is a strong correlation between the

measured concentration of ROS and carbon chain length as well as the degree of saturation

and to a smaller extent engine operating conditions.

This highlights the importance of knowing the surface chemistry of particles for assessing

their health impacts. It also sheds a light onto new aspects of particulate emissions that

should be taken into account when establishing relevant metrics for health implications of

emissions from various future fuels.

9.2 Directions for future research

As stated earlier, the work presented in this thesis demonstrated confirmed

applicability of BPEAnit in detecting particle-derived ROS and, therefore, estimating the

oxidative potential of PM; investigated the chemical mechanisms that are switching on the

fluorescence of BPEAnit upon exposure to aerosols; and identified the products that are

formed during those processes.

Several other cell-free approaches have been used by researchers to explore

oxidative potential of PM in a quantitative manner. They all have certain limitations, do not

provide directly comparable results and, to date, none of these assays has been

acknowledged as the best acellular assay and none have yet been widely adopted for

investigation of potential PM toxicity. Therefore it is crucial to compare the performance of

all the probes that are used for evaluating the OP. This will provide information on the

sensitivity, linearity and repeatability of each acellular probe and also if the results different

probes provide can be comparable. Although all the probes use different units for

expressing redox properties of PM and their reactivity is being triggered by different

249

physico-chemical properties of PM, the possibility of comparing the trends among different

samples or even the possible complementary analysis would allow researchers to compare

and understand their results and to get more information on the processes behind the

reported results.

Diesel engine combustion and cigarette smoke are primary particulate sources. In

addition to the primary PM sources it would be beneficial to investigate secondary PM-

secondary organic aerosols (SOA). Flow reactors are convenient for generating SOA and can

enable us to further explore the importance of secondary organics condensed on PM. In

addition the Aerosol Mass Spectrometer (also available at ILAQH) will be used to estimate

the (secondary) organic aerosol mass fraction. In this way we will be able to compare the

AMS derived organic mass fraction with the ROS concentration.

Moreover, it is also crucial to investigate the influence of the atmospheric aging

processes on DEP originating from different fuels and engine technologies. This would

presume the investigation on how different aging factors influence partitioning of SVOC

between gas and particle phase. This would include studying the dynamics of SVOCs emitted

from diesel engines for various atmospheric dilution conditions and the influence UV light

and ozone will play in altering the chemical composition of PM organic fraction. The next

step following this study would be the estimation of OP of aged DEP.

It would be also interesting to investigate how different after-treatment technologies

affect volatile and semi volatile organic fraction and the evolution of OP when these

technologies are applied.

On the other hand, improvement in the sampling methodology for OP

measurements needs to be considered as well. Liquid impingement has been found to be a

very good sampling technique, which enables particles to rapidly and directly react with the

radical quencher BPEAnit, thus limiting possible changes in chemical properties of particles

arising during the time between sampling, extracting and analysis.

However, as previous research showed that impingers have relatively low and size

dependent collection efficiency for particles smaller than 0.5 µm, the current sampling

technique could also be improved. A potentially suitable method for particle collection

250

would be the Particle Into Liquid Sampler (PILS). This method grows submicron particles in a

condensation growth chamber and subsequently collects them using a wetted wall cyclone.

This method was first introduced by Orsini (Orsini, Rhoads et al. 2008) and could be a

promising methodology for a real-time ROS monitor.

In addition to this, BPEAnit has only been used in non-biological samples. The next

step in its role would be investigation of oxidative stress generated by PM in cell exposure

assays. Success in this application would allow employment of this assay as a rapid test for

oxidative potential of PM within cells.

doctor of philosophy april , 201 3 · miloš crnjanski, sumatra. ii abstract pollution in the...

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